no code implementations • COLING 2022 • Suhe Wang, Xiaoyuan Liu, Bo Liu, Diwen Dong
Meta-learning has emerged as an effective approach for few-shot text classification.
no code implementations • COLING 2022 • Bo Liu, Wandi Xu, Yuejia Xiang, XiaoJun Wu, Lejian He, BoWen Zhang, Li Zhu
However, we find that noise learning in text classification is relatively underdeveloped: 1. many methods that have been proven effective in the image domain are not explored in text classification, 2. it is difficult to conduct a fair comparison between previous studies as they do experiments in different noise settings.
no code implementations • COLING 2022 • Xin Guan, Biwei Cao, Qingqing Gao, Zheng Yin, Bo Liu, Jiuxin Cao
In this paper, we propose a novel model, Co-Reasoning Network (CORN), which adopts a bidirectional multi-level connection structure based on Co-Attention Transformer.
no code implementations • ECCV 2020 • Hongyuan Du, Linjun Li, Bo Liu, Nuno Vasconcelos
The sparsity of point clouds limits deep learning models on capturing long-range dependencies, which makes features extracted by the models ambiguous.
no code implementations • NAACL (TextGraphs) 2021 • Yuejia Xiang, Yunyan Zhang, Xiaoming Shi, Bo Liu, Wandi Xu, Xi Chen
Then, a selection module is employed to choose those most relative facts in an autoregressive manner, giving a preliminary order for the retrieved facts.
no code implementations • 23 May 2024 • Huajian Xin, Daya Guo, Zhihong Shao, Zhizhou Ren, Qihao Zhu, Bo Liu, Chong Ruan, Wenda Li, Xiaodan Liang
Proof assistants like Lean have revolutionized mathematical proof verification, ensuring high accuracy and reliability.
no code implementations • 21 May 2024 • Weijia Liu, Bo Miao, Jiuxin Cao, Xuelin Zhu, Bo Liu, Mehwish Nasim, Ajmal Mian
Specifically, LMR introduces a context enhancement technique with LLMs to generate crucial target-related context semantics.
no code implementations • 21 May 2024 • Yan He, Bing Tu, Bo Liu, Jun Li, Antonio Plaza
To overcome the limitations of traditional Mamba, which is confined to modeling causal sequences and inadaptable to high-dimensional scenarios, a 3D-Spectral-Spatial Selective Scanning (3DSS) mechanism is introduced, which performs pixel-wise selective scanning on 3D hyperspectral tokens along the spectral and spatial dimensions.
no code implementations • 6 May 2024 • Bo Liu, Shanshan Qin, Venkatesh Murthy, Yuhai Tu
We next compared the alignment performance of local Hebbian rule and the global stochastic-gradient-descent (SGD) learning for artificial neural networks.
2 code implementations • 9 Apr 2024 • Li-Ming Zhan, Bo Liu, Xiao-Ming Wu
Out-of-distribution (OOD) detection plays a crucial role in ensuring the safety and reliability of deep neural networks in various applications.
Out-of-Distribution Detection Out of Distribution (OOD) Detection +4
no code implementations • 30 Mar 2024 • Bo Liu, Lemeng Wu, Lizhang Chen, Kaizhao Liang, Jiaxu Zhu, Chen Liang, Raghuraman Krishnamoorthi, Qiang Liu
The Lion optimizer has been a promising competitor with the AdamW for training large AI models, with advantages on memory, computation, and sample efficiency.
no code implementations • 26 Mar 2024 • Jingyu Xu, Binbin Wu, Jiaxin Huang, Yulu Gong, Yifan Zhang, Bo Liu
With the explosive growth and diversification of medical data, as well as the continuous improvement of medical needs and challenges, artificial intelligence technology is playing an increasingly important role in the medical field.
1 code implementation • 23 Mar 2024 • Daijun Ding, Li Dong, Zhichao Huang, Guangning Xu, Xu Huang, Bo Liu, Liwen Jing, BoWen Zhang
To address these issues, we propose an encoder-decoder data augmentation (EDDA) framework.
no code implementations • 20 Mar 2024 • Yulu Gong, Jiaxin Huang, Bo Liu, Jingyu Xu, Binbin Wu, Yifan Zhang
Overall, the paragraph effectively communicates the importance of machine learning technology in addressing resource allocation and virtual machine migration challenges in cloud computing.
no code implementations • 18 Mar 2024 • William Watson, Bo Liu
Table extraction has long been a pervasive problem in financial services.
no code implementations • 11 Mar 2024 • Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, Jihong Guan
This paper is an extended abstract of our original work published in KDD23, where we won the best research paper award (Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, and Jihong Guan.
no code implementations • 9 Mar 2024 • Chen Li, Haotian Zheng, Yiping Sun, Cangqing Wang, Liqiang Yu, Che Chang, Xinyu Tian, Bo Liu
In the realm of computational knowledge representation, Knowledge Graph Reasoning (KG-R) stands at the forefront of facilitating sophisticated inferential capabilities across multifarious domains.
no code implementations • 9 Mar 2024 • Liqiang Yu, Chen Li, Bo Liu, Chang Che
This paper focuses on recognizing dialed numbers in a touch-tone telephone system based on the Dual Tone MultiFrequency (DTMF) signaling technique with analysis of stochastic aspects during the noise and random duration of characters.
2 code implementations • 8 Mar 2024 • Haoyu Lu, Wen Liu, Bo Zhang, Bingxuan Wang, Kai Dong, Bo Liu, Jingxiang Sun, Tongzheng Ren, Zhuoshu Li, Hao Yang, Yaofeng Sun, Chengqi Deng, Hanwei Xu, Zhenda Xie, Chong Ruan
The DeepSeek-VL family (both 1. 3B and 7B models) showcases superior user experiences as a vision-language chatbot in real-world applications, achieving state-of-the-art or competitive performance across a wide range of visual-language benchmarks at the same model size while maintaining robust performance on language-centric benchmarks.
Ranked #31 on Visual Question Answering on MM-Vet
no code implementations • 7 Mar 2024 • Weihuang Liu, Xi Shen, Haolun Li, Xiuli Bi, Bo Liu, Chi-Man Pun, Xiaodong Cun
In this work, we introduce a test-time training (TTT) strategy to address the problem.
no code implementations • 3 Mar 2024 • Tu Luan, Victoria Cepeda, Bo Liu, Zac Bowen, Ujjwal Ayyangar, Mathieu Almeida, Christopher M. Hill, Sergey Koren, Todd J. Treangen, Adam Porter, Mihai Pop
Metagenomic studies have primarily relied on de novo assembly for reconstructing genes and genomes from microbial mixtures.
2 code implementations • 27 Feb 2024 • Wenhao Tang, Fengtao Zhou, Sheng Huang, Xiang Zhu, Yi Zhang, Bo Liu
Unlike existing works that focus on pre-training powerful feature extractor or designing sophisticated instance aggregator, R$^2$T is tailored to re-embed instance features online.
no code implementations • 27 Feb 2024 • Yifan Zhang, Bo Liu, Yulu Gong, Jiaxin Huang, Jingyu Xu, Weixiang Wan
Each user requests the cloud computing center to use a certain number of cloud resources at a specific time.
no code implementations • 25 Feb 2024 • Bo Liu, Grace Li Zhang, Xunzhao Yin, Ulf Schlichtmann, Bing Li
In this new design, the multipliers are replaced by simple logic gates to project the results onto a wide bit representation.
1 code implementation • 6 Feb 2024 • Xixi Hu, Bo Liu, Xingchao Liu, Qiang Liu
To address this challenge, we propose AdaFlow, an imitation learning framework based on flow-based generative modeling.
no code implementations • 30 Jan 2024 • Weixiang Wan, Wenjian Sun, Qiang Zeng, Linying Pan, Jingyu Xu, Bo Liu
In the era of Internet of Things, how to develop a smart sensor system with sustainable power supply, easy deployment and flexible use has become a difficult problem to be solved.
no code implementations • 26 Jan 2024 • Shulin Li, Liqiang Yu, Bo Liu, Qunwei Lin, Jiaxin Huang
However, at present, there are few studies on the diagnosis of early lung cancer by AI technology combined with SCT scanning.
1 code implementation • 17 Jan 2024 • Bo Liu, Rachita Chhaparia, Arthur Douillard, Satyen Kale, Andrei A. Rusu, Jiajun Shen, Arthur Szlam, Marc'Aurelio Ranzato
Local stochastic gradient descent (Local-SGD), also referred to as federated averaging, is an approach to distributed optimization where each device performs more than one SGD update per communication.
no code implementations • 17 Jan 2024 • Tian Liu, Yue Cui, Xueyang Hu, Yecheng Xu, Bo Liu
In this paper, we formulate and investigate the impact of inaccessible nodes to GL under a dynamic network topology.
no code implementations • 6 Jan 2024 • Liqiang Yu, Bo Liu, Qunwei Lin, Xinyu Zhao, Chang Che
In the realm of patent document analysis, assessing semantic similarity between phrases presents a significant challenge, notably amplifying the inherent complexities of Cooperative Patent Classification (CPC) research.
no code implementations • 6 Jan 2024 • Jiaxin Huang, Xinyu Zhao, Chang Che, Qunwei Lin, Bo Liu
To address the specific needs of ELLs, we propose the use of DeBERTa, a state-of-the-art neural language model, for improving automated feedback tools.
1 code implementation • 5 Jan 2024 • DeepSeek-AI, :, Xiao Bi, Deli Chen, Guanting Chen, Shanhuang Chen, Damai Dai, Chengqi Deng, Honghui Ding, Kai Dong, Qiushi Du, Zhe Fu, Huazuo Gao, Kaige Gao, Wenjun Gao, Ruiqi Ge, Kang Guan, Daya Guo, JianZhong Guo, Guangbo Hao, Zhewen Hao, Ying He, Wenjie Hu, Panpan Huang, Erhang Li, Guowei Li, Jiashi Li, Yao Li, Y. K. Li, Wenfeng Liang, Fangyun Lin, A. X. Liu, Bo Liu, Wen Liu, Xiaodong Liu, Xin Liu, Yiyuan Liu, Haoyu Lu, Shanghao Lu, Fuli Luo, Shirong Ma, Xiaotao Nie, Tian Pei, Yishi Piao, Junjie Qiu, Hui Qu, Tongzheng Ren, Zehui Ren, Chong Ruan, Zhangli Sha, Zhihong Shao, Junxiao Song, Xuecheng Su, Jingxiang Sun, Yaofeng Sun, Minghui Tang, Bingxuan Wang, Peiyi Wang, Shiyu Wang, Yaohui Wang, Yongji Wang, Tong Wu, Y. Wu, Xin Xie, Zhenda Xie, Ziwei Xie, Yiliang Xiong, Hanwei Xu, R. X. Xu, Yanhong Xu, Dejian Yang, Yuxiang You, Shuiping Yu, Xingkai Yu, B. Zhang, Haowei Zhang, Lecong Zhang, Liyue Zhang, Mingchuan Zhang, Minghua Zhang, Wentao Zhang, Yichao Zhang, Chenggang Zhao, Yao Zhao, Shangyan Zhou, Shunfeng Zhou, Qihao Zhu, Yuheng Zou
The rapid development of open-source large language models (LLMs) has been truly remarkable.
1 code implementation • 4 Jan 2024 • William Yue, Bo Liu, Peter Stone
Deep generative replay has emerged as a promising approach for continual learning in decision-making tasks.
no code implementations • 2 Jan 2024 • Xuelin Zhu, Jian Liu, Dongqi Tang, Jiawei Ge, Weijia Liu, Bo Liu, Jiuxin Cao
Identifying labels that did not appear during training, known as multi-label zero-shot learning, is a non-trivial task in computer vision.
no code implementations • 21 Dec 2023 • Qing Zhang, Cheng Liu, Bo Liu, Haitong Huang, Ying Wang, Huawei Li, Xiaowei Li
Fault-tolerant deep learning accelerator is the basis for highly reliable deep learning processing and critical to deploy deep learning in safety-critical applications such as avionics and robotics.
no code implementations • 20 Dec 2023 • Bo Liu, Liqiang Yu, Chang Che, Qunwei Lin, Hao Hu, Xinyu Zhao
This paper focuses on the analysis of the application effectiveness of the integration of deep learning and computer vision technologies.
no code implementations • 20 Dec 2023 • Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu, Philip S. Thomas, Bruno Castro da Silva
In this paper, we introduce a fresh perspective on the challenges of credit assignment and policy evaluation.
no code implementations • 7 Dec 2023 • Xuelin Zhu, Jiuxin Cao, Jian Liu, Dongqi Tang, Furong Xu, Weijia Liu, Jiawei Ge, Bo Liu, Qingpei Guo, Tianyi Zhang
Pre-trained vision-language models have notably accelerated progress of open-world concept recognition.
no code implementations • 28 Nov 2023 • Jiawei Ge, Xiangmei Chen, Jiuxin Cao, Xuelin Zhu, Bo Liu
However, current VL trackers have not fully exploited the power of VL learning, as they suffer from limitations such as heavily relying on off-the-shelf backbones for feature extraction, ineffective VL fusion designs, and the absence of VL-related loss functions.
1 code implementation • 28 Nov 2023 • Jiaxin Lu, Hao Kang, Haoxiang Li, Bo Liu, Yiding Yang, QiXing Huang, Gang Hua
Generation-based methods that generate grasping postures conditioned on the object can often produce diverse grasping, but they are insufficient for high grasping success due to lack of discriminative information.
no code implementations • 19 Nov 2023 • Lei Wang, Bo Liu, Yinchi Ma, Fangfang Liang, Nawei Guo
Gait recognition has achieved promising advances in controlled settings, yet it significantly struggles in unconstrained environments due to challenges such as view changes, occlusions, and varying walking speeds.
no code implementations • 7 Nov 2023 • Huan Tian, Guangsheng Zhang, Bo Liu, Tianqing Zhu, Ming Ding, Wanlei Zhou
It leverages the difference in the predictions from both the original and fairness-enhanced models and exploits the observed prediction gaps as attack clues.
no code implementations • 2 Nov 2023 • Xiuli Bi, Bo Liu, Fan Yang, Bin Xiao, Weisheng Li, Gao Huang, Pamela C. Cosman
This paper approaches the generated image detection problem from a new perspective: Start from real images.
1 code implementation • 24 Oct 2023 • Yuyang Li, Bo Liu, Yiran Geng, Puhao Li, Yaodong Yang, Yixin Zhu, Tengyu Liu, Siyuan Huang
The intricate kinematics of the human hand enable simultaneous grasping and manipulation of multiple objects, essential for tasks such as object transfer and in-hand manipulation.
no code implementations • 24 Oct 2023 • Jianghong Zhou, Bo Liu, Jhalak Nilesh Acharya Yao Hong, Kuang-Chih Lee, Musen Wen
In the dynamic field of eCommerce, the quality and comprehensiveness of product descriptions are pivotal for enhancing search visibility and customer engagement.
1 code implementation • 23 Oct 2023 • Yujie Feng, Zexin Lu, Bo Liu, LiMing Zhan, Xiao-Ming Wu
In this study, we conduct an initial examination of ChatGPT's capabilities in DST.
1 code implementation • 16 Oct 2023 • Yang Wu, Shenglong Hu, Huihui Song, Kaihua Zhang, Bo Liu, Dong Liu
To simultaneously consider the uncertainty introduced by irrelevant images and the consensus features of the remaining relevant images in the group, we designed a latent variable generator branch and CoSOD transformer branch.
1 code implementation • 13 Oct 2023 • Xiangyu Zhao, Bo Liu, Qijiong Liu, Guangyuan Shi, Xiao-Ming Wu
We present EasyGen, an efficient model designed to enhance multimodal understanding and generation by harnessing the capabilities of diffusion models and large language models (LLMs), Unlike existing multimodal models that predominately depend on encoders like CLIP or ImageBind and need ample amounts of training data to bridge modalities, EasyGen leverages BiDiffuser, a bidirectional conditional diffusion model, to foster more efficient modality interactions.
1 code implementation • 12 Oct 2023 • Miao Zhu, Qiming Fu, Bo Liu, Mengxi Zhang, Bojian Li, Xiaoyan Luo, Fugen Zhou
In this study, a novel imaging method RT-SRTS is proposed which integrates 3D imaging and tumor segmentation into one network based on multi-task learning (MTL) and achieves real-time simultaneous 3D reconstruction and tumor segmentation from a single X-ray projection at any angle.
no code implementations • 9 Oct 2023 • Lizhang Chen, Bo Liu, Kaizhao Liang, Qiang Liu
As we can expect from the results of a random search program, Lion incorporates elements from several existing algorithms, including signed momentum, decoupled weight decay, Polak, and Nesterov momentum, but does not fit into any existing category of theoretically grounded optimizers.
no code implementations • 25 Sep 2023 • Tongtong Yuan, Xuange Zhang, Kun Liu, Bo Liu, Chen Chen, Jian Jin, Zhenzhen Jiao
Furthermore, we benchmark SOTA models for four multimodal tasks on this newly created dataset, which serve as new baselines for surveillance video-and-language understanding.
no code implementations • 18 Sep 2023 • Tianyi Song, Jiuxin Cao, Kun Wang, Bo Liu, Xiaofeng Zhang
The current state-of-the-art method combines the features of historical captions, historical frames, and the current captions as conditions for generating the current frame.
no code implementations • ICCV 2023 • Lei Fan, Bo Liu, Haoxiang Li, Ying Wu, Gang Hua
First, prediction uncertainty should be separately quantified as confusion depicting inter-class uncertainties and ignorance identifying out-of-distribution samples.
1 code implementation • 20 Aug 2023 • Bo Liu, LiMing Zhan, Zexin Lu, Yujie Feng, Lei Xue, Xiao-Ming Wu
Out-of-distribution (OOD) detection plays a vital role in enhancing the reliability of machine learning (ML) models.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
1 code implementation • 18 Aug 2023 • Xiaoxiao He, Chaowei Tan, Ligong Han, Bo Liu, Leon Axel, Kang Li, Dimitris N. Metaxas
However, current cardiac MRI-based reconstruction technology used in clinical settings is 2D with limited through-plane resolution, resulting in low-quality reconstructed cardiac volumes.
no code implementations • 16 Aug 2023 • Xinghua Xue, Cheng Liu, Bo Liu, Haitong Huang, Ying Wang, Tao Luo, Lei Zhang, Huawei Li, Xiaowei Li
When it is applied on fault-tolerant neural networks enhanced with fault-aware retraining and constrained activation functions, the resulting model accuracy generally shows significant improvement in presence of various faults.
no code implementations • 3 Aug 2023 • Fangkai Yang, Wenjie Yin, Lu Wang, Tianci Li, Pu Zhao, Bo Liu, Paul Wang, Bo Qiao, Yudong Liu, Mårten Björkman, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang
However, they suffer from poor data quality like data missing in model training and prediction, which limits the performance.
no code implementations • 29 Jul 2023 • Yibo Wang, Yanbing Xue, Bo Liu, Musen Wen, Wenting Zhao, Stephen Guo, Philip S. Yu
Position bias, the phenomenon whereby users tend to focus on higher-ranked items of the search result list regardless of the actual relevance to queries, is prevailing in many ranking systems.
1 code implementation • ICCV 2023 • Wenhao Tang, Sheng Huang, Xiaoxian Zhang, Fengtao Zhou, Yi Zhang, Bo Liu
Moreover, the student is used to update the teacher with an exponential moving average (EMA), which in turn identifies new hard instances for subsequent training iterations and stabilizes the optimization.
no code implementations • ICCV 2023 • Lei Wang, Bo Liu, Fangfang Liang, Bincheng Wang
While current methods focus on exploiting body part-based representations, they often neglect the hierarchical dependencies between local motion patterns.
1 code implementation • 4 Jul 2023 • Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, Jihong Guan
Inspired by the prompt learning in natural language processing (NLP), which has presented significant effectiveness in leveraging prior knowledge for various NLP tasks, we study the prompting topic for graphs with the motivation of filling the gap between pre-trained models and various graph tasks.
1 code implementation • 20 Jun 2023 • Haitong Huang, Cheng Liu, Bo Liu, Xinghua Xue, Huawei Li, Xiaowei Li
It enables users to modify an independent fault configuration file rather than neural network models for the fault injection and vulnerability analysis.
no code implementations • 19 Jun 2023 • Minghe Zhang, Chaosheng Dong, Jinmiao Fu, Tianchen Zhou, Jia Liang, Jia Liu, Bo Liu, Michinari Momma, Bryan Wang, Yan Gao, Yi Sun
In this paper, we introduce AdaSelection, an adaptive sub-sampling method to identify the most informative sub-samples within each minibatch to speed up the training of large-scale deep learning models without sacrificing model performance.
no code implementations • 15 Jun 2023 • Xue Yang, Zifeng Liu, Xiaohu Tang, Rongxing Lu, Bo Liu
With the emergence of privacy leaks in federated learning, secure aggregation protocols that mainly adopt either homomorphic encryption or threshold secret sharing have been widely developed for federated learning to protect the privacy of the local training data of each client.
no code implementations • 13 Jun 2023 • Lan Wang, Ruiling He, Lili Zhao, Jia Wang, Zhengzi Geng, Tao Ren, Guo Zhang, Peng Zhang, Kaiqiang Tang, Chaofei Gao, Fei Chen, Liting Zhang, Yonghe Zhou, Xin Li, Fanbin He, Hui Huan, Wenjuan Wang, Yunxiao Liang, Juan Tang, Fang Ai, Tingyu Wang, Liyun Zheng, Zhongwei Zhao, Jiansong Ji, Wei Liu, Jiaojiao Xu, Bo Liu, Xuemei Wang, Yao Zhang, Qiong Yan, Muhan Lv, Xiaomei Chen, Shuhua Zhang, Yihua Wang, Yang Liu, Li Yin, Yanni Liu, Yanqing Huang, Yunfang Liu, Kun Wang, Meiqin Su, Li Bian, Ping An, Xin Zhang, Linxue Qian, Shao Li, Xiaolong Qi
Validation analysis revealed that the AUCs of DLRP were 0. 91 for GEV (95% CI 0. 90 to 0. 93, p < 0. 05) and 0. 88 for HRV (95% CI 0. 86 to 0. 89, p < 0. 01), which were significantly and robustly better than canonical risk indicators, including the value of LSM and SSM.
1 code implementation • 10 Jun 2023 • Li Xu, Bo Liu, Ameer Hamza Khan, Lu Fan, Xiao-Ming Wu
With the availability of large-scale, comprehensive, and general-purpose vision-language (VL) datasets such as MSCOCO, vision-language pre-training (VLP) has become an active area of research and proven to be effective for various VL tasks such as visual-question answering.
1 code implementation • NeurIPS 2023 • Bo Liu, Yihao Feng, Peter Stone, Qiang Liu
One of the grand enduring goals of AI is to create generalist agents that can learn multiple different tasks from diverse data via multitask learning (MTL).
no code implementations • 11 May 2023 • Aneeq Zia, Kiran Bhattacharyya, Xi Liu, Max Berniker, Ziheng Wang, Rogerio Nespolo, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Bo Liu, David Austin, Yiheng Wang, Michal Futrega, Jean-Francois Puget, Zhenqiang Li, Yoichi Sato, Ryo Fujii, Ryo Hachiuma, Mana Masuda, Hideo Saito, An Wang, Mengya Xu, Mobarakol Islam, Long Bai, Winnie Pang, Hongliang Ren, Chinedu Nwoye, Luca Sestini, Nicolas Padoy, Maximilian Nielsen, Samuel Schüttler, Thilo Sentker, Hümeyra Husseini, Ivo Baltruschat, Rüdiger Schmitz, René Werner, Aleksandr Matsun, Mugariya Farooq, Numan Saaed, Jose Renato Restom Viera, Mohammad Yaqub, Neil Getty, Fangfang Xia, Zixuan Zhao, Xiaotian Duan, Xing Yao, Ange Lou, Hao Yang, Jintong Han, Jack Noble, Jie Ying Wu, Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Herag Arabian, Ning Ding, Knut Moeller, Weiliang Chen, Quan He, Muhammad Bilal, Taofeek Akinosho, Adnan Qayyum, Massimo Caputo, Hunaid Vohra, Michael Loizou, Anuoluwapo Ajayi, Ilhem Berrou, Faatihah Niyi-Odumosu, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel, Anthony Jarc
Unfortunately, obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task.
1 code implementation • 10 May 2023 • Chengkun Wei, Minghu Zhao, Zhikun Zhang, Min Chen, Wenlong Meng, Bo Liu, Yuan Fan, Wenzhi Chen
We also explore some improvements that can maintain model utility and defend against MIAs more effectively.
no code implementations • 10 May 2023 • Xin Guan, Biwei Cao, Qingqing Gao, Zheng Yin, Bo Liu, Jiuxin Cao
Commonsense question answering (QA) research requires machines to answer questions based on commonsense knowledge.
1 code implementation • 22 Apr 2023 • Bo Liu, Yuqian Jiang, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, Peter Stone
LLM+P takes in a natural language description of a planning problem, then returns a correct (or optimal) plan for solving that problem in natural language.
no code implementations • 5 Apr 2023 • Yanbing Xue, Bo Liu, Weizhi Du, Jayanth Korlimarla, Musen Men
In this paper, we first propose data and feature engineering techniques to handle the aforementioned problems in ad system; after that, we evaluate the benefit of our practical framework on real-world data sets from our traffic logs from online shopping site.
no code implementations • 31 Mar 2023 • Biwei Cao, Lulu Hua, Jiuxin Cao, Jie Gui, Bo Liu, James Tin-Yau Kwok
Different from popular methods which take full advantage of the propagation topology structure, in this paper, we propose a novel framework for fake news detection from perspectives of semantic, emotion and data enhancement, which excavates the emotional evolution patterns of news participants during the propagation process, and a dual deep interaction channel network of semantic and emotion is designed to obtain a more comprehensive and fine-grained news representation with the consideration of comments.
no code implementations • 28 Mar 2023 • Tao He, Sheng Huang, Wenhao Tang, Bo Liu
DKE employs a segmentation module to segment the shrunken text region as the text kernel, then expands the text kernel contour to obtain text boundary by regressing the vertex-wise offsets.
1 code implementation • 25 Mar 2023 • Xiaoxiao He, Chaowei Tan, Bo Liu, Liping Si, Weiwu Yao, Liang Zhao, Di Liu, Qilong Zhangli, Qi Chang, Kang Li, Dimitris N. Metaxas
The supervised learning of the proposed method extracts features from limited labeled data in each client, while the unsupervised data is used to distill both feature and response-based knowledge from a national data repository to further improve the accuracy of the collaborative model and reduce the communication cost.
no code implementations • 23 Mar 2023 • Huajie Chen, Tianqing Zhu, Yuan Zhao, Bo Liu, Xin Yu, Wanlei Zhou
By avoiding high-frequency artifacts and manipulating the frequency distribution of the embedded feature map, LIDS achieves improved robustness against attacks that distort the high-frequency components of container images.
no code implementations • 10 Mar 2023 • Jiaqi Xu, Bo Liu, Yunkuo Chen, Mengli Cheng, Xing Shi
Specifically, we design a Text-Guided MultiWay-Sampler based on adapt-pooling residual mapping and self-attention modules to sample long sequences and fuse multi-modal features, which reduces the computational costs and addresses performance degradation caused by previous samplers.
Ranked #1 on TGIF-Transition on TGIF-QA (using extra training data)
no code implementations • 11 Feb 2023 • Yixing Liu, Yan Sun, Zhengtao Ding, Li Shen, Bo Liu, DaCheng Tao
Federated learning (FL), as a collaborative distributed training paradigm with several edge computing devices under the coordination of a centralized server, is plagued by inconsistent local stationary points due to the heterogeneity of the local partial participation clients, which precipitates the local client-drifts problems and sparks off the unstable and slow convergence, especially on the aggravated heterogeneous dataset.
1 code implementation • CVPR 2023 • Bin Xiao, Yang Hu, Bo Liu, Xiuli Bi, Weisheng Li, Xinbo Gao
Since their binarization processes are not a component of the network, the learning-based binary descriptor cannot fully utilize the advances of deep learning.
no code implementations • CVPR 2023 • Yang Wu, Huihui Song, Bo Liu, Kaihua Zhang, Dong Liu
To address this issue, this paper presents a group exchange-masking (GEM) strategy for robust CoSOD model learning.
no code implementations • ICCV 2023 • Yunqian Wen, Bo Liu, Jingyi Cao, Rong Xie, Li Song
To address these issues, we propose IDeudemon, which employs a "divide and conquer" strategy to protect identity and preserve utility step by step while maintaining good explainability.
no code implementations • ICCV 2023 • Xuelin Zhu, Jian Liu, Weijia Liu, Jiawei Ge, Bo Liu, Jiuxin Cao
Multi-label image classification refers to assigning a set of labels for an image.
no code implementations • CVPR 2023 • Leming Guo, Wanli Xue, Qing Guo, Bo Liu, Kaihua Zhang, Tiantian Yuan, ShengYong Chen
Existing results in [9, 20, 25, 36] have indicated that, as the frontal component of the overall model, the spatial perception module used for spatial feature extraction tends to be insufficiently trained.
Ranked #6 on Sign Language Recognition on CSL-Daily
no code implementations • ICCV 2023 • Tiankang Su, Huihui Song, Dong Liu, Bo Liu, Qingshan Liu
We integrate our offline training and online fine-tuning in a unified framework for unsupervised video object segmentation and dub our method Online Adversarial Self-Tuning (OAST).
no code implementations • 7 Dec 2022 • Bo Liu, Rongmei Yang, Hao Wang, Linyuan Lü
This study reports for the first time a complete cavity map of C. elegans neural network, developing a new method for mining higher-order structures that can be applied by researchers in neuroscience, network science and other interdisciplinary fields to explore higher-order structural markers of complex systems.
no code implementations • 21 Nov 2022 • Shiqiang Zhu, Ting Yu, Tao Xu, Hongyang Chen, Schahram Dustdar, Sylvain Gigan, Deniz Gunduz, Ekram Hossain, Yaochu Jin, Feng Lin, Bo Liu, Zhiguo Wan, Ji Zhang, Zhifeng Zhao, Wentao Zhu, Zuoning Chen, Tariq Durrani, Huaimin Wang, Jiangxing Wu, Tongyi Zhang, Yunhe Pan
In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications.
no code implementations • 19 Nov 2022 • Bo Liu, Jianfeng Zhang, Wenpeng Luan, Zishuai Liu, Yixin Yu
Load event detection is the fundamental step for the event-based non-intrusive load monitoring (NILM).
no code implementations • 16 Nov 2022 • Biwei Cao, Jiuxin Cao, Jie Gui, Jiayun Shen, Bo Liu, Lei He, Yuan Yan Tang, James Tin-Yau Kwok
Such approaches, however, ignore the VE's unique nature of relation inference between the premise and hypothesis.
1 code implementation • 13 Nov 2022 • Jie Ren, Xidong Feng, Bo Liu, Xuehai Pan, Yao Fu, Luo Mai, Yaodong Yang
TorchOpt further provides a high-performance distributed execution runtime.
no code implementations • 11 Nov 2022 • Yunpeng Zhao, Fugen Zhou, Bin Guo, Bo Liu
The proposed spatial temporal graph convolution block directly exploits BOLD time series as input features, which provides an interesting view for rsfMRI-based preclinical AD diagnosis.
no code implementations • 20 Oct 2022 • Guangsheng Zhang, Bo Liu, Huan Tian, Tianqing Zhu, Ming Ding, Wanlei Zhou
As a booming research area in the past decade, deep learning technologies have been driven by big data collected and processed on an unprecedented scale.
1 code implementation • 10 Oct 2022 • Zifan Xu, Bo Liu, Xuesu Xiao, Anirudh Nair, Peter Stone
Deep reinforcement learning (RL) has brought many successes for autonomous robot navigation.
1 code implementation • ACMMM 2022 • Xuelin Zhu, Jiuxin Cao, Jiawei Ge, Weijia Liu, Bo Liu
Specifically, in each layer of TSFormer, a cross-modal attention module is developed to aggregate visual features from spatial stream into semantic stream and update label semantics via a residual connection.
no code implementations • 19 Sep 2022 • Mao Ye, Bo Liu, Stephen Wright, Peter Stone, Qiang Liu
Bilevel optimization (BO) is useful for solving a variety of important machine learning problems including but not limited to hyperparameter optimization, meta-learning, continual learning, and reinforcement learning.
1 code implementation • 18 Sep 2022 • Lei Wang, Bo Liu, Bincheng Wang, Fuqiang Yu
In this study, we propose a multi-granularity motion representation network (GaitMM) for gait sequence learning.
2 code implementations • 17 Aug 2022 • Bo Liu, Yihao Feng, Qiang Liu, Peter Stone
Furthermore, we introduce the metric residual network (MRN) that deliberately decomposes the action-value function Q(s, a, g) into the negated summation of a metric plus a residual asymmetric component.
no code implementations • 25 Jul 2022 • Feng Yang, Xingle Zhang, Bo Liu
Among the current popular MOT methods based on deep learning, Detection Based Tracking (DBT) is the most widely used in industry, and the performance of them depend on their object detection network.
3 code implementations • 21 Jun 2022 • Jiayi Weng, Min Lin, Shengyi Huang, Bo Liu, Denys Makoviichuk, Viktor Makoviychuk, Zichen Liu, Yufan Song, Ting Luo, Yukun Jiang, Zhongwen Xu, Shuicheng Yan
EnvPool is open-sourced at https://github. com/sail-sg/envpool.
1 code implementation • 23 May 2022 • Jiazhi Xu, Sheng Huang, Fengtao Zhou, Luwen Huangfu, Daniel Zeng, Bo Liu
Then, the MLIC models of fewer categories are trained with these sub-tasks in parallel for respectively learning the joint patterns and the category-specific patterns of labels.
no code implementations • 6 May 2022 • Bo Liu
With the rapid development of mobile Internet and big data, a huge amount of data is generated in the network, but the data that users are really interested in a very small portion.
no code implementations • 11 Apr 2022 • Akarsh Kumar, Bo Liu, Risto Miikkulainen, Peter Stone
GESMR co-evolves a population of solutions and a population of MRs, such that each MR is assigned to a group of solutions.
no code implementations • 30 Mar 2022 • Bo Liu, Lihua Hu, Qiulei Dong, Zhanyi Hu
How to generate pseudo labels for unseen-class samples and how to use such usually noisy pseudo labels are two critical issues in transductive learning.
1 code implementation • 24 Mar 2022 • Bo Liu, Qiang Liu, Peter Stone
As intelligent agents become autonomous over longer periods of time, they may eventually become lifelong counterparts to specific people.
no code implementations • 17 Mar 2022 • Bo Liu, Qiulei Dong, Zhanyi Hu
Firstly, we propose a Semantic-diversity transfer Network (SetNet) addressing the first two limitations, where 1) a multiple-attention architecture and a diversity regularizer are proposed to learn multiple local visual features that are more consistent with semantic attributes and 2) a projector ensemble that geometrically takes diverse local features as inputs is proposed to model visual-semantic relations from diverse local perspectives.
no code implementations • 13 Mar 2022 • Dayong Ye, Sheng Shen, Tianqing Zhu, Bo Liu, Wanlei Zhou
The experimental results show the method to be an effective and timely defense against both membership inference and model inversion attacks with no reduction in accuracy.
no code implementations • 13 Mar 2022 • Dayong Ye, Tianqing Zhu, Shuai Zhou, Bo Liu, Wanlei Zhou
In launching a contemporary model inversion attack, the strategies discussed are generally based on either predicted confidence score vectors, i. e., black-box attacks, or the parameters of a target model, i. e., white-box attacks.
no code implementations • 21 Feb 2022 • Zhenxin Wu, Jiazheng Gong, Kecen Guo, Guanye Liang, Qingliang Che, Bo Liu
Aspect-based sentiment classification (ABSC) is a very challenging subtask of sentiment analysis (SA) and suffers badly from the class-imbalance.
no code implementations • 19 Feb 2022 • Shahaf S. Shperberg, Bo Liu, Peter Stone
When humans make catastrophic mistakes, they are expected to learn never to repeat them, such as a toddler who touches a hot stove and immediately learns never to do so again.
1 code implementation • 12 Feb 2022 • Fan Lu, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang
Our approach can be seamlessly integrated with existing latent space based methods and be potentially applied in any product retrieval method that uses purchase history to model user preferences.
no code implementations • 1 Feb 2022 • Daoming Lyu, Bo Liu, Jianshu Chen
We consider the problem of multi-task reasoning (MTR), where an agent can solve multiple tasks via (first-order) logic reasoning.
no code implementations • 24 Jan 2022 • Liangliang Xu, Daoming Lyu, Yangchen Pan, Aiwen Jiang, Bo Liu
This paper proposes Short-Term VOlatility-controlled Policy Search (STOPS), a novel algorithm that solves risk-averse problems by learning from short-term trajectories instead of long-term trajectories.
no code implementations • 14 Jan 2022 • Bo Liu, Lihua Hu, Zhanyi Hu, Qiulei Dong
This work is a systematical analysis on the so-called hard class problem in zero-shot learning (ZSL), that is, some unseen classes disproportionally affect the ZSL performances than others, as well as how to remedy the problem by detecting and exploiting hard classes.
no code implementations • 31 Dec 2021 • Zheng Zhang, Liangliang Xu, Levent Yilmaz, Bo Liu
Despite recent advances in modern machine learning algorithms, the opaqueness of their underlying mechanisms continues to be an obstacle in adoption.
BIG-bench Machine Learning Explainable artificial intelligence +2
1 code implementation • 31 Dec 2021 • Xidong Feng, Bo Liu, Jie Ren, Luo Mai, Rui Zhu, Haifeng Zhang, Jun Wang, Yaodong Yang
Gradient-based Meta-RL (GMRL) refers to methods that maintain two-level optimisation procedures wherein the outer-loop meta-learner guides the inner-loop gradient-based reinforcement learner to achieve fast adaptations.
1 code implementation • NeurIPS 2021 • Xidong Feng, Oliver Slumbers, Ziyu Wan, Bo Liu, Stephen Mcaleer, Ying Wen, Jun Wang, Yaodong Yang
When solving two-player zero-sum games, multi-agent reinforcement learning (MARL) algorithms often create populations of agents where, at each iteration, a new agent is discovered as the best response to a mixture over the opponent population.
Multi-agent Reinforcement Learning Vocal Bursts Valence Prediction
no code implementations • 30 Nov 2021 • Virginia Adams, Hoo-chang Shin, Carol Anderson, Bo Liu, Anas Abidin
We extend our BERT-based approach to the entity linking task.
no code implementations • 30 Nov 2021 • Virginia Adams, Hoo-chang Shin, Carol Anderson, Bo Liu, Anas Abidin
In Track-1 of the BioCreative VII Challenge participants are asked to identify interactions between drugs/chemicals and proteins.
no code implementations • 30 Nov 2021 • Carol Anderson, Bo Liu, Anas Abidin, Hoo-chang Shin, Virginia Adams
Social media posts contain potentially valuable information about medical conditions and health-related behavior.
no code implementations • 25 Nov 2021 • Kingsley Nweye, Bo Liu, Peter Stone, Zoltan Nagy
Building upon prior research that highlighted the need for standardizing environments for building control research, and inspired by recently introduced challenges for real life reinforcement learning control, here we propose a non-exhaustive set of nine real world challenges for reinforcement learning control in grid-interactive buildings.
Model Predictive Control Multi-agent Reinforcement Learning +2
no code implementations • 24 Nov 2021 • Chen Huang, Ruisi He, Bo Ai, Andreas F. Molisch, Buon Kiong Lau, Katsuyuki Haneda, Bo Liu, Cheng-Xiang Wang, Mi Yang, Claude Oestges, Zhangdui Zhong
This two-part paper investigates the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels.
no code implementations • 24 Nov 2021 • Chen Huang, Ruisi He, Bo Ai, Andreas F. Molisch, Buon Kiong Lau, Katsuyuki Haneda, Bo Liu, Cheng-Xiang Wang, Mi Yang, Claude Oestges, Zhangdui Zhong
To provide higher data rates, as well as better coverage, cost efficiency, security, adaptability, and scalability, the 5G and beyond 5G networks are developed with various artificial intelligence techniques.
3 code implementations • NeurIPS 2021 • Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, Qiang Liu
The goal of multi-task learning is to enable more efficient learning than single task learning by sharing model structures for a diverse set of tasks.
1 code implementation • ICCV 2021 • Zhirui Dai, Yuepeng Jiang, Yi Li, Bo Liu, Antoni B. Chan, Nuno Vasconcelos
A dataset of crowd scenes with people annotations under a bird's eye view (BEV) and ground truth for metric distances is introduced, and several measures for the evaluation of social distance detection systems are proposed.
no code implementations • 9 Oct 2021 • Qishen Ha, Bo Liu, Hongwei Zhang
We present our solutions to the Google Landmark Challenges 2021, for both the retrieval and the recognition tracks.
no code implementations • 4 Oct 2021 • Bo Li, Peng Qi, Bo Liu, Shuai Di, Jingen Liu, JiQuan Pei, JinFeng Yi, BoWen Zhou
In this review, we provide AI practitioners with a comprehensive guide for building trustworthy AI systems.
no code implementations • 1 Oct 2021 • Ahmet F. Budak, Prateek Bhansali, Bo Liu, Nan Sun, David Z. Pan, Chandramouli V. Kashyap
The key contributions of this paper are a novel sample-efficient two-stage deep learning optimization framework leveraging RL actor-critic algorithms, and a recipe to extend it on large industrial circuits using critical device identification.
no code implementations • 24 Aug 2021 • Brandon Leung, Chih-Hui Ho, Amir Persekian, David Orozco, Yen Chang, Erik Sandstrom, Bo Liu, Nuno Vasconcelos
Second, it is used to show that the augmentation of in the wild datasets, such as ImageNet, with in the lab data, such as OOWL500, can significantly decrease these biases, leading to object recognizers of improved generalization.
no code implementations • 13 Aug 2021 • Daoming Lyu, Fangkai Yang, Hugh Kwon, Wen Dong, Levent Yilmaz, Bo Liu
Human-robot interactive decision-making is increasingly becoming ubiquitous, and trust is an influential factor in determining the reliance on autonomy.
3 code implementations • 8 Jul 2021 • Bo Liu, Chaowei Tan, Jiazhou Wang, Tao Zeng, Huasong Shan, Houpu Yao, Heng Huang, Peng Dai, Liefeng Bo, Yanqing Chen
We use this platform to demonstrate our research and development results on privacy preserving machine learning algorithms.
no code implementations • 8 Jul 2021 • Shuang Deng, Qiulei Dong, Bo Liu, Zhanyi Hu
The proposed network is iteratively updated with its predicted pseudo labels, where a superpoint generation module is introduced for extracting superpoints from 3D point clouds, and a pseudo-label optimization module is explored for automatically assigning pseudo labels to the unlabeled points under the constraint of the extracted superpoints.
1 code implementation • 7 Jul 2021 • Shuang Deng, Bo Liu, Qiulei Dong, Zhanyi Hu
Many recent works show that a spatial manipulation module could boost the performances of deep neural networks (DNNs) for 3D point cloud analysis.
no code implementations • 1 Jul 2021 • Bo Liu, Shuang Deng, Qiulei Dong, Zhanyi Hu
In this work, a language-level Semantics Conditioned framework for 3D Point cloud segmentation, called SeCondPoint, is proposed, where language-level semantics are introduced to condition the modeling of point feature distribution as well as the pseudo-feature generation, and a feature-geometry-based mixup approach is further proposed to facilitate the distribution learning.
no code implementations • CVPR 2021 • Kaihua Zhang, Mingliang Dong, Bo Liu, Xiao-Tong Yuan, Qingshan Liu
This dense correlation volumes enables the network to accurately discover the structured pair-wise pixel similarities among the common salient objects.
no code implementations • ACL 2021 • Li-Ming Zhan, Haowen Liang, Bo Liu, Lu Fan, Xiao-Ming Wu, Albert Y. S. Lam
Since the distribution of outlier utterances is arbitrary and unknown in the training stage, existing methods commonly rely on strong assumptions on data distribution such as mixture of Gaussians to make inference, resulting in either complex multi-step training procedures or hand-crafted rules such as confidence threshold selection for outlier detection.
1 code implementation • 14 Jun 2021 • Jingru Yi, Pengxiang Wu, Hui Tang, Bo Liu, Qiaoying Huang, Hui Qu, Lianyi Han, Wei Fan, Daniel J. Hoeppner, Dimitris N. Metaxas
To deal with this problem, in this paper, we propose an object-guided instance segmentation method.
1 code implementation • 4 Jun 2021 • Xidong Feng, Oliver Slumbers, Ziyu Wan, Bo Liu, Stephen Mcaleer, Ying Wen, Jun Wang, Yaodong Yang
When solving two-player zero-sum games, multi-agent reinforcement learning (MARL) algorithms often create populations of agents where, at each iteration, a new agent is discovered as the best response to a mixture over the opponent population.
1 code implementation • 18 May 2021 • Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Animashree Anandkumar
Specifically, we 1) adopt the attention mechanism for both the coach and the players; 2) propose a variational objective to regularize learning; and 3) design an adaptive communication method to let the coach decide when to communicate with the players.
Multi-agent Reinforcement Learning reinforcement-learning +3
no code implementations • ICCV 2021 • Bo Liu, Haoxiang Li, Hao Kang, Gang Hua, Nuno Vasconcelos
A new learning algorithm is then proposed for GeometrIc Structure Transfer (GIST), with resort to a combination of loss functions that combine class-balanced and random sampling to guarantee that, while overfitting to the popular classes is restricted to geometric parameters, it is leveraged to transfer class geometry from popular to few-shot classes.
no code implementations • 1 May 2021 • Bo Liu, Mandar Dixit, Roland Kwitt, Gang Hua, Nuno Vasconcelos
In the absence of dense pose sampling in image space, these latent space trajectories provide cross-modal guidance for learning.
no code implementations • 1 May 2021 • Bo Liu, Haoxiang Li, Hao Kang, Nuno Vasconcelos, Gang Hua
A consistency loss has been introduced to limit the impact from unlabeled data while leveraging them to update the feature embedding.
no code implementations • 1 May 2021 • Bo Liu, Haoxiang Li, Hao Kang, Gang Hua, Nuno Vasconcelos
It is shown that, unlike class-balanced sampling, this is an adversarial augmentation strategy.
no code implementations • 12 Mar 2021 • Hanyu Xue, Bo Liu, Ming Ding, Tianqing Zhu, Dayong Ye, Li Song, Wanlei Zhou
The excessive use of images in social networks, government databases, and industrial applications has posed great privacy risks and raised serious concerns from the public.
no code implementations • 2 Mar 2021 • Yunqian Wen, Li Song, Bo Liu, Ming Ding, Rong Xie
We propose IdentityDP, a face anonymization framework that combines a data-driven deep neural network with a differential privacy (DP) mechanism.
no code implementations • 25 Feb 2021 • Bo Liu
A motivating example is given to explain the reason for the existence of spurious local minima: each output neuron of deep fully-connected networks and CNNs with piecewise linear activations produces a continuous piecewise linear (CPWL) output, and different pieces of CPWL output can fit disjoint groups of data samples when minimizing the empirical risk.
2 code implementations • 18 Feb 2021 • Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu
We show that SLAKE can be used to facilitate the development and evaluation of Med-VQA systems.
1 code implementation • NeurIPS 2020 • Lemeng Wu, Bo Liu, Peter Stone, Qiang Liu
We propose firefly neural architecture descent, a general framework for progressively and dynamically growing neural networks to jointly optimize the networks' parameters and architectures.
no code implementations • 13 Jan 2021 • Yunqi Li, Shuyuan Xu, Bo Liu, Zuohui Fu, Shuchang Liu, Xu Chen, Yongfeng Zhang
This paper proposes a discrete knowledge graph (KG) embedding (DKGE) method, which projects KG entities and relations into the Hamming space based on a computationally tractable discrete optimization algorithm, to solve the formidable storage and computation cost challenges in traditional continuous graph embedding methods.
no code implementations • ICCV 2021 • Kaihua Zhang, Zicheng Zhao, Dong Liu, Qingshan Liu, Bo Liu
The popular unsupervised video object segmentation methods fuse the RGB frame and optical flow via a two-stream network.
Ranked #4 on Unsupervised Video Object Segmentation on FBMS test
no code implementations • 1 Jan 2021 • Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar
The performance of our method is comparable or even better than the setting where all players have a full view of the environment, but no coach.
no code implementations • ICCV 2021 • Jingyi Cao, Bo Liu, Yunqian Wen, Rong Xie, Li Song
The popularization of intelligent devices including smartphones and surveillance cameras results in more serious privacy issues.
no code implementations • 3 Dec 2020 • Bo Liu, Ranglei Wu, Xiuli Bi, Bin Xiao, Weisheng Li, Guoyin Wang, Xinbo Gao
The unfixed encoder autonomously learns the image fingerprints that differentiate between the tampered and non-tampered regions, whereas the fixed encoder intentionally provides the direction information that assists the learning and detection of the network.
no code implementations • NeurIPS 2020 • Deheng Ye, Guibin Chen, Wen Zhang, Sheng Chen, Bo Yuan, Bo Liu, Jia Chen, Zhao Liu, Fuhao Qiu, Hongsheng Yu, Yinyuting Yin, Bei Shi, Liang Wang, Tengfei Shi, Qiang Fu, Wei Yang, Lanxiao Huang, Wei Liu
However, existing work falls short in handling the raw game complexity caused by the explosion of agent combinations, i. e., lineups, when expanding the hero pool in case that OpenAI's Dota AI limits the play to a pool of only 17 heroes.
no code implementations • 24 Nov 2020 • Bo Liu, Ming Ding, Sina Shaham, Wenny Rahayu, Farhad Farokhi, Zihuai Lin
The newly emerged machine learning (e. g. deep learning) methods have become a strong driving force to revolutionize a wide range of industries, such as smart healthcare, financial technology, and surveillance systems.
no code implementations • 13 Nov 2020 • Fan Yu, Zhuoyuan Yao, Xiong Wang, Keyu An, Lei Xie, Zhijian Ou, Bo Liu, Xiulin Li, Guanqiong Miao
Automatic speech recognition (ASR) has been significantly advanced with the use of deep learning and big data.
Sound Audio and Speech Processing
no code implementations • NeurIPS 2021 • Sihang Guo, Ruohan Zhang, Bo Liu, Yifeng Zhu, Mary Hayhoe, Dana Ballard, Peter Stone
1) How similar are the visual representations learned by RL agents and humans when performing the same task?
1 code implementation • COLING 2020 • Ziheng Zhang, Jiaoyan Chen, Xi Chen, Hualuo Liu, Yuejia Xiang, Bo Liu, Yefeng Zheng
Embedding-based entity alignment has been widely investigated in recent years, but most proposed methods still rely on an ideal supervised learning setting with a large number of unbiased seed mappings for training and validation, which significantly limits their usage.
no code implementations • 17 Oct 2020 • Mariusz Bojarski, Chenyi Chen, Joyjit Daw, Alperen Değirmenci, Joya Deri, Bernhard Firner, Beat Flepp, Sachin Gogri, Jesse Hong, Lawrence Jackel, Zhenhua Jia, BJ Lee, Bo Liu, Fei Liu, Urs Muller, Samuel Payne, Nischal Kota Nagendra Prasad, Artem Provodin, John Roach, Timur Rvachov, Neha Tadimeti, Jesper van Engelen, Haiguang Wen, Eric Yang, Zongyi Yang
Four years ago, an experimental system known as PilotNet became the first NVIDIA system to steer an autonomous car along a roadway.
2 code implementations • 11 Oct 2020 • Qishen Ha, Bo Liu, Fuxu Liu, Peiyuan Liao
We present our third place solution to the Google Landmark Recognition 2020 competition.
4 code implementations • 11 Oct 2020 • Qishen Ha, Bo Liu, Fuxu Liu
We present our winning solution to the SIIM-ISIC Melanoma Classification Challenge.
1 code implementation • 21 Sep 2020 • Fei Xie, Wankou Yang, Bo Liu, Kaihua Zhang, Wanli Xue, WangMeng Zuo
Existing visual object tracking usually learns a bounding-box based template to match the targets across frames, which cannot accurately learn a pixel-wise representation, thereby being limited in handling severe appearance variations.
no code implementations • 17 Sep 2020 • Zhenyu Wang, Z. -X. Li, Ruifang Wang, Bo Liu, Hao Meng, Yunshan Cao, Peng Yan
We propose a new method to generate magnetic skyrmions through spin-wave focusing in chiral ferromagnets. A lens is constructed to focus spin waves by a curved interface between two ferromagnetic thin films with different perpendicular magnetic anisotropies.
Mesoscale and Nanoscale Physics
no code implementations • 14 Sep 2020 • Daoming Lyu, Qi Qi, Mohammad Ghavamzadeh, Hengshuai Yao, Tianbao Yang, Bo Liu
To achieve variance-reduced off-policy-stable policy optimization, we propose an algorithm family that is memory-efficient, stochastically variance-reduced, and capable of learning from off-policy samples.
no code implementations • 29 Aug 2020 • Bo Liu, Qiulei Dong, Zhanyi Hu
In addition, considering that the visual features from categorization CNNs are generally inconsistent with their semantic features, a simple feature selection strategy is introduced for extracting more compact semantic visual features.
1 code implementation • 17 Aug 2020 • Jingru Yi, Pengxiang Wu, Bo Liu, Qiaoying Huang, Hui Qu, Dimitris Metaxas
To address this issue, in this work we extend the horizontal keypoint-based object detector to the oriented object detection task.
Ranked #11 on Oriented Object Detection on DOTA 1.0
no code implementations • ECCV 2020 • Hongduan Tian, Bo Liu, Xiao-Tong Yuan, Qingshan Liu
To remedy this deficiency, we propose a network pruning based meta-learning approach for overfitting reduction via explicitly controlling the capacity of network.
1 code implementation • 4 Jul 2020 • Chuan Ma, Jun Li, Ming Ding, Bo Liu, Kang Wei, Jian Weng, H. Vincent Poor
Generative adversarial network (GAN) has attracted increasing attention recently owing to its impressive ability to generate realistic samples with high privacy protection.
no code implementations • 15 Jun 2020 • Bo Liu
The existence of local minima for one-hidden-layer ReLU networks has been investigated theoretically in [8].
1 code implementation • 6 Jun 2020 • Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik
In this paper, we introduce proximal gradient temporal difference learning, which provides a principled way of designing and analyzing true stochastic gradient temporal difference learning algorithms.
no code implementations • 6 Jun 2020 • Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik
In this paper, we analyze the convergence rate of the gradient temporal difference learning (GTD) family of algorithms.
no code implementations • NeurIPS 2012 • Bo Liu, Sridhar Mahadevan, Ji Liu
We present a novel $l_1$ regularized off-policy convergent TD-learning method (termed RO-TD), which is able to learn sparse representations of value functions with low computational complexity.
no code implementations • 6 Jun 2020 • Daoming Lyu, Bo Liu, Matthieu Geist, Wen Dong, Saad Biaz, Qi. Wang
Policy evaluation algorithms are essential to reinforcement learning due to their ability to predict the performance of a policy.
no code implementations • 31 May 2020 • Feifan Lv, Bo Liu, Feng Lu
This paper proposes a new light-weight convolutional neural network (5k parameters) for non-uniform illumination image enhancement to handle color, exposure, contrast, noise and artifacts, etc., simultaneously and effectively.
no code implementations • 29 May 2020 • Rongfang Wang, Fan Ding, Licheng Jiao, Jia-Wei Chen, Bo Liu, Wenping Ma, Mi Wang
We verify our light-weighted neural network on four sets of bitemporal SAR images.
1 code implementation • CVPR 2020 • Bo Liu, Hao Kang, Haoxiang Li, Gang Hua, Nuno Vasconcelos
It is argued that the classic softmax classifier is a poor solution for open-set recognition, since it tends to overfit on the training classes.
no code implementations • 22 May 2020 • Jia-Wei Chen, Rongfang Wang, Fan Ding, Bo Liu, Licheng Jiao, Jie Zhang
Furthermore, to verify the generalization of the proposed method, we apply our proposed method to the cross-dataset bitemporal SAR image change detection, where the MSSP network (MSSP-Net) is trained on a dataset and then applied to an unknown testing dataset.
1 code implementation • 22 Apr 2020 • Shangtong Zhang, Bo Liu, Shimon Whiteson
We present a mean-variance policy iteration (MVPI) framework for risk-averse control in a discounted infinite horizon MDP optimizing the variance of a per-step reward random variable.
no code implementations • 31 Mar 2020 • Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, Peter Stone
Existing autonomous robot navigation systems allow robots to move from one point to another in a collision-free manner.
1 code implementation • CVPR 2020 • Chih-Hui Ho, Bo Liu, Tz-Ying Wu, Nuno Vasconcelos
Multiview recognition has been well studied in the literature and achieves decent performance in object recognition and retrieval task.
1 code implementation • 26 Mar 2020 • Hengchao Wang, Bo Liu, Yan Zhang, Fan Jiang, Yuwei Ren, Lijuan Yin, Hangwei Liu, Sen Wang, Wei Fan
We show that corrected third-generation data can be used to count k-mer frequencies and estimate genome size reliably, in replacement of using second-generation data.
1 code implementation • CVPR 2020 • Kaihua Zhang, Tengpeng Li, Shiwen Shen, Bo Liu, Jin Chen, Qingshan Liu
Second, we develop an attention graph clustering algorithm to discriminate the common objects from all the salient foreground objects in an unsupervised fashion.
no code implementations • 13 Mar 2020 • Kaihua Zhang, Long Wang, Dong Liu, Bo Liu, Qingshan Liu, Zhu Li
We present an end-to-end network which stores short- and long-term video sequence information preceding the current frame as the temporal memories to address the temporal modeling in VOS.
no code implementations • 7 Mar 2020 • Bo Liu, Mengya Shen
Geometry and topology of decision regions are closely related with classification performance and robustness against adversarial attacks.
no code implementations • 12 Feb 2020 • Bo Liu
For one-hidden-layer ReLU networks, we prove that all differentiable local minima are global inside differentiable regions.
1 code implementation • ICML 2020 • Shangtong Zhang, Bo Liu, Shimon Whiteson
Namely, the optimization problem in GenDICE is not a convex-concave saddle-point problem once nonlinearity in optimization variable parameterization is introduced to ensure positivity, so any primal-dual algorithm is not guaranteed to converge or find the desired solution.
1 code implementation • 2 Jan 2020 • Jin Chen, Huihui Song, Kaihua Zhang, Bo Liu, Qingshan Liu
Due to a variety of motions across different frames, it is highly challenging to learn an effective spatiotemporal representation for accurate video saliency prediction (VSP).
1 code implementation • 29 Nov 2019 • Kaihua Zhang, Jin Chen, Bo Liu, Qingshan Liu
With the multi-resolution features of the relevant images as input, we design a spatial modulator to learn a mask for each image.
1 code implementation • 21 Nov 2019 • Ligong Han, Ruijiang Gao, Mun Kim, Xin Tao, Bo Liu, Dimitris Metaxas
Conditional generative adversarial networks have shown exceptional generation performance over the past few years.
no code implementations • 20 Nov 2019 • Jingru Yi, Hui Tang, Pengxiang Wu, Bo Liu, Daniel J. Hoeppner, Dimitris N. Metaxas, Lianyi Han, Wei Fan
Along with the instance normalization, the model is able to recover the target object distribution and suppress the distribution of neighboring attached objects.
1 code implementation • 19 Nov 2019 • Yuxiang Ren, Bo Liu, Chao Huang, Peng Dai, Liefeng Bo, Jiawei Zhang
The derived node representations can be used to serve various downstream tasks, such as node classification and node clustering.
Ranked #7 on Heterogeneous Node Classification on DBLP (PACT) 14k
no code implementations • 18 Nov 2019 • Ke He, Bo Liu, Yu Zhang, Andrew Ling, Dian Gu
In this paper, we firstly propose the FeCaffe, i. e. FPGA-enabled Caffe, a hierarchical software and hardware design methodology based on the Caffe to enable FPGA to support mainline deep learning development features, e. g. training and inference with Caffe.
1 code implementation • ICML 2020 • Shangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson
With the help of the emphasis critic and the canonical value function critic, we show convergence for COF-PAC, where the critics are linear and the actor can be nonlinear.
1 code implementation • 28 Sep 2019 • Yunbo Wang, Bo Liu, Jiajun Wu, Yuke Zhu, Simon S. Du, Li Fei-Fei, Joshua B. Tenenbaum
A major difficulty of solving continuous POMDPs is to infer the multi-modal distribution of the unobserved true states and to make the planning algorithm dependent on the perceived uncertainty.
no code implementations • 25 Sep 2019 • Hongduan Tian, Bo Liu, Xiao-Tong Yuan, Qingshan Liu
Meta-Learning has achieved great success in few-shot learning.
no code implementations • 18 Sep 2019 • Daoming Lyu, Fangkai Yang, Bo Liu, Steven Gustafson
Recent successes of Reinforcement Learning (RL) allow an agent to learn policies that surpass human experts but suffers from being time-hungry and data-hungry.
no code implementations • 9 Sep 2019 • Bo Liu, Yi Liang
We consider in this paper the optimal approximations of convex univariate functions with feed-forward Relu neural networks.
no code implementations • 19 Aug 2019 • Yanshan Xiao, HuaiPei Wang, Bo Liu
Learning with label proportions (LLP), which is a learning task that only provides unlabeled data in bags and each bag's label proportion, has widespread successful applications in practice.
1 code implementation • 22 Jul 2019 • Jingru Yi, Pengxiang Wu, Qiaoying Huang, Hui Qu, Bo Liu, Daniel J. Hoeppner, Dimitris N. Metaxas
In this paper, we propose a new box-based cell instance segmentation method.
no code implementations • 17 Jun 2019 • Daoming Lyu, Fangkai Yang, Bo Liu, Steven Gustafson
Conventional reinforcement learning (RL) allows an agent to learn policies via environmental rewards only, with a long and slow learning curve, especially at the beginning stage.
no code implementations • 6 Jun 2019 • Qiulei Dong, Bo Liu, Zhanyi Hu
Recently DCNN (Deep Convolutional Neural Network) has been advocated as a general and promising modelling approach for neural object representation in primate inferotemporal cortex.
no code implementations • 30 May 2019 • Xiang Li, Chan Lu, Danni Cheng, Wei-Hong Li, Mei Cao, Bo Liu, Jiechao Ma, Wei-Shi Zheng
Visible watermark plays an important role in image copyright protection and the robustness of a visible watermark to an attack is shown to be essential.