no code implementations • 17 Mar 2024 • Xuetong Li, Yuan Gao, Hong Chang, Danyang Huang, Yingying Ma, Rui Pan, Haobo Qi, Feifei Wang, Shuyuan Wu, Ke Xu, Jing Zhou, Xuening Zhu, Yingqiu Zhu, Hansheng Wang
A huge amount of statistical methods for massive data computation have been rapidly developed in the past decades.
no code implementations • 27 Feb 2024 • Xue Yang, Changchun Bao, Jing Zhou, Xianhong Chen
These weighting matrices reflect the similarity among different frames of the T-F representations and are further employed to obtain the consistent T-F representations of the enrollment.
no code implementations • 11 Jan 2024 • Litian Li, Jord Molhoek, Jing Zhou
A subset of unsuccessful intention-to-speak cases in the data is annotated.
no code implementations • 28 Nov 2023 • Jintang Li, Jiawang Dan, Ruofan Wu, Jing Zhou, Sheng Tian, Yunfei Liu, Baokun Wang, Changhua Meng, Weiqiang Wang, Yuchang Zhu, Liang Chen, Zibin Zheng
Over the past few years, graph neural networks (GNNs) have become powerful and practical tools for learning on (static) graph-structure data.
no code implementations • 18 Oct 2023 • Jintang Li, Zheng Wei, Jiawang Dan, Jing Zhou, Yuchang Zhu, Ruofan Wu, Baokun Wang, Zhang Zhen, Changhua Meng, Hong Jin, Zibin Zheng, Liang Chen
Through in-depth investigations on several real-world heterogeneous graphs exhibiting varying levels of heterophily, we have observed that heterogeneous graph neural networks (HGNNs), which inherit many mechanisms from GNNs designed for homogeneous graphs, fail to generalize to heterogeneous graphs with heterophily or low level of homophily.
no code implementations • 27 Aug 2023 • Xiaotong Fu, Xiangyu Meng, Jing Zhou, Ying Ji
Lung cancer, particularly in its advanced stages, remains a leading cause of death globally.
no code implementations • 27 Aug 2023 • Jing Zhou, Xiaotong Fu, Xirong Li, Wei Feng, Zhang Zhang, Ying Ji
The most common type of lung cancer, lung adenocarcinoma (LUAD), has been increasingly detected since the advent of low-dose computed tomography screening technology.
1 code implementation • 14 May 2023 • Qijie Wei, Jingyuan Yang, Bo wang, Jinrui Wang, Jianchun Zhao, Xinyu Zhao, Sheng Yang, Niranchana Manivannan, Youxin Chen, Dayong Ding, Jing Zhou, Xirong Li
This paper addresses the emerging task of recognizing multiple retinal diseases from wide-field (WF) and ultra-wide-field (UWF) fundus images.
no code implementations • 28 Nov 2022 • Zongcheng Liu, Jiangshuai Huang, Changyun Wen, Jing Zhou, Xiucai Huang
A novel control design framework is proposed for a class of non-Lipschitz nonlinear systems with quantized states, meanwhile prescribed transient performance and lower control design complexity could be guaranteed.
no code implementations • 23 Nov 2022 • Jing Zhou, Xinru Jing, Muyu Liu, Hansheng Wang
This leads to a benchmark model, which we then use to obtain the predicted class probabilities for each sample in a dataset.
1 code implementation • 15 Nov 2022 • Haike Xu, Zongyu Lin, Jing Zhou, Yanan Zheng, Zhilin Yang
In the finetuning setting, our approach also achieves new state-of-the-art results on a wide range of NLP tasks, with only 1/4 parameters of previous methods.
1 code implementation • Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence 2022 • Xiang Huang, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Bin Dong, Lei Chen
In recent years, deep learning technology has been used to solve partial differential equations (PDEs), among which the physics-informed neural networks (PINNs)method emerges to be a promising method for solving both forward and inverse PDE problems.
no code implementations • 28 Mar 2022 • Jing Zhou, Changchun Bao
One is that the sub-array decomposition is adopted to improve the accuracy of MSW-DOA estimation by minimizing the weighted error, and the other one is that the frequency focusing procedure is optimized according to the presence probability of sound sources for reducing the influence of the sub-bands with low signal to noise ratio (SNR).
no code implementations • 15 Dec 2021 • Xueying Zhang, Yanyan Zou, Hainan Zhang, Jing Zhou, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Xueqi He, Yun Xiao, Bo Long, Han Yu, Lingfei Wu
It consists of two main components: 1) natural language generation, which is built from a transformer-pointer network and a pre-trained sequence-to-sequence model based on millions of training data from our in-house platform; and 2) copywriting quality control, which is based on both automatic evaluation and human screening.
no code implementations • 15 Nov 2021 • Gengxiang Chen, Yingguang Li, Xu Liu, Qinglu Meng, Jing Zhou, Xiaozhong Hao
During the curing process of composites, the temperature history heavily determines the evolutions of the field of degree of cure as well as the residual stress, which will further influence the mechanical properties of composite, thus it is important to simulate the real temperature history to optimize the curing process of composites.
no code implementations • 2 Nov 2021 • Xiang Huang, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Bingya Weng, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Lei Chen, Bin Dong
In recent years, deep learning technology has been used to solve partial differential equations (PDEs), among which the physics-informed neural networks (PINNs) emerges to be a promising method for solving both forward and inverse PDE problems.
1 code implementation • ACL 2022 • Yanan Zheng, Jing Zhou, Yujie Qian, Ming Ding, Chonghua Liao, Jian Li, Ruslan Salakhutdinov, Jie Tang, Sebastian Ruder, Zhilin Yang
The few-shot natural language understanding (NLU) task has attracted much recent attention.
1 code implementation • ACL 2022 • Jing Zhou, Yanan Zheng, Jie Tang, Jian Li, Zhilin Yang
Most previous methods for text data augmentation are limited to simple tasks and weak baselines.
no code implementations • 9 Feb 2021 • Marija Tepegjozova, Jing Zhou, Gerda Claeskens, Claudia Czado
Further, we show that the nonparametric conditional quantile estimator is consistent.
Methodology
no code implementations • 20 Jan 2021 • Jing Zhou, Jialun Ping
This observation implies that the Schwinger effect within an anisotropic background is comparatively weaker when contrasted with its manifestation in an isotropic background. Finally, we also find that the Schwinger effect in the transverse direction is weakened compared to the parallel direction in the anisotropic background, which is consistent with the top-down model.
High Energy Physics - Theory
1 code implementation • 1 Jan 2021 • Haobo Qi, Jing Zhou, Hansheng Wang
Deep neural network (DNN) models often involve features of ultrahigh dimensions.
no code implementations • 12 Jun 2020 • Jing Zhou, Gerda Claeskens, Jelena Bradic
We find, however, that model-averaged and composite quantile estimators often outperform least-squares methods, even in the case of Gaussian model noise.
1 code implementation • 12 May 2020 • Jing Pan, Wendao Liu, Jing Zhou
The freedom of fast iterations of distributed deep learning tasks is crucial for smaller companies to gain competitive advantages and market shares from big tech giants.
no code implementations • ICML 2020 • Keizo Kato, Jing Zhou, Tomotake Sasaki, Akira Nakagawa
We show our method has the following properties: (i) the Jacobian matrix between the input space and a Euclidean latent space forms a constantlyscaled orthonormal system and enables isometric data embedding; (ii) the relation of PDFs in both spaces can become tractable one such as proportional relation.
3 code implementations • 30 Sep 2019 • Jehandad Khan, Paul Fultz, Artem Tamazov, Daniel Lowell, Chao Liu, Michael Melesse, Murali Nandhimandalam, Kamil Nasyrov, Ilya Perminov, Tejash Shah, Vasilii Filippov, Jing Zhang, Jing Zhou, Bragadeesh Natarajan, Mayank Daga
Deep Learning has established itself to be a common occurrence in the business lexicon.
no code implementations • 25 Sep 2019 • Keizo Kato, Jing Zhou, Akira Nakagawa
In the generative model approach of machine learning, it is essential to acquire an accurate probabilistic model and compress the dimension of data for easy treatment.
no code implementations • 6 Jul 2017 • Fenglong Ma, Radha Chitta, Saurabh Kataria, Jing Zhou, Palghat Ramesh, Tong Sun, Jing Gao
Question answering is an important and difficult task in the natural language processing domain, because many basic natural language processing tasks can be cast into a question answering task.
no code implementations • 19 Jun 2017 • Fenglong Ma, Radha Chitta, Jing Zhou, Quanzeng You, Tong Sun, Jing Gao
Existing work solves this problem by employing recurrent neural networks (RNNs) to model EHR data and utilizing simple attention mechanism to interpret the results.
no code implementations • 18 Oct 2016 • Josep Crego, Jungi Kim, Guillaume Klein, Anabel Rebollo, Kathy Yang, Jean Senellart, Egor Akhanov, Patrice Brunelle, Aurelien Coquard, Yongchao Deng, Satoshi Enoue, Chiyo Geiss, Joshua Johanson, Ardas Khalsa, Raoum Khiari, Byeongil Ko, Catherine Kobus, Jean Lorieux, Leidiana Martins, Dang-Chuan Nguyen, Alexandra Priori, Thomas Riccardi, Natalia Segal, Christophe Servan, Cyril Tiquet, Bo wang, Jin Yang, Dakun Zhang, Jing Zhou, Peter Zoldan
Since the first online demonstration of Neural Machine Translation (NMT) by LISA, NMT development has recently moved from laboratory to production systems as demonstrated by several entities announcing roll-out of NMT engines to replace their existing technologies.
no code implementations • 3 May 2016 • Jing Zhou, Xiaopeng Hong, Fei Su, Guoying Zhao
To overcome this problem, we propose a real-time regression framework based on the recurrent convolutional neural network for automatic frame-level pain intensity estimation.