1 code implementation • 2 Nov 2023 • Boyang Wang, Bowen Liu, Shiyu Liu, Fengyu Yang
In this work, we for the first time, present a video compression-based degradation model to synthesize low-resolution image data in the blind SISR task.
no code implementations • 5 Jul 2023 • Shiyu Liu, Shaogao Lv, Dun Zeng, Zenglin Xu, Hui Wang, Yue Yu
Federated learning is a decentralized and privacy-preserving technique that enables multiple clients to collaborate with a server to learn a global model without exposing their private data.
no code implementations • 5 Jul 2023 • Shaogao Lv, Gang Wen, Shiyu Liu, Linsen Wei, Ming Li
Overall, our research highlights the importance of integrating feature and graph information alignment in GSL, as inspired by our derived theoretical result, and showcases the superiority of our approach in handling noisy graph structures through comprehensive experiments on real-world datasets.
no code implementations • 20 May 2023 • Shiyu Liu, Linsen Wei, Shaogao Lv, Ming Li
For a single-layer GCN, we establish an explicit theoretical understanding of GCN with the $\ell_p$-regularized stochastic learning by analyzing the stability of our SGD proximal algorithm.
1 code implementation • CVPR 2023 • Bowen Liu, Yu Chen, Rakesh Chowdary Machineni, Shiyu Liu, Hun-Seok Kim
In this paper, we propose multi-mode video compression (MMVC), a block wise mode ensemble deep video compression framework that selects the optimal mode for feature domain prediction adapting to different motion patterns.
no code implementations • 2 Mar 2023 • Dun Zeng, Xiangjing Hu, Shiyu Liu, Yue Yu, Qifan Wang, Zenglin Xu
Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices.
no code implementations • 9 Dec 2022 • Shiyu Liu, Rohan Ghosh, Dylan Tan, Mehul Motani
However, in network pruning, we find that the sparsity introduced by ReLU, which we quantify by a term called dynamic dead neuron rate (DNR), is not beneficial for the pruned network.
no code implementations • 9 Dec 2022 • Shiyu Liu, Rohan Ghosh, Mehul Motani
In this paper, we propose a new forecasting strategy called Generative Forecasting (GenF), which generates synthetic data for the next few time steps and then makes long-range forecasts based on generated and observed data.
no code implementations • 9 Dec 2022 • Shiyu Liu, Mehul Motani
MRwMR-BUR-CLF further improves the classification performance by 3. 8%- 5. 5% (relative to MRwMR), and it also outperforms three popular classifier dependent feature selection methods.
no code implementations • 9 Dec 2022 • Shiyu Liu, Rohan Ghosh, John Tan Chong Min, Mehul Motani
(ii) In addition to the strong theoretical motivation, SILO is empirically optimal in the sense of matching an Oracle, which exhaustively searches for the optimal value of max_lr via grid search.
no code implementations • 26 May 2022 • Dun Zeng, Shiyu Liu, Siqi Liang, Zonghang Li, Hui Wang, Irwin King, Zenglin Xu
However, privacy information could be leaked from uploaded gradients and be exposed to malicious attackers or an honest-but-curious server.
no code implementations • 9 Mar 2022 • Andrea Bejarano-Carbo, Hyochan An, Kyojin Choo, Shiyu Liu, Qirui Zhang, Dennis Sylvester, David Blaauw, Hun-Seok Kim
Millimeter-scale embedded sensing systems have unique advantages over larger devices as they are able to capture, analyze, store, and transmit data at the source while being unobtrusive and covert.
no code implementations • 17 Oct 2021 • Shiyu Liu, Chong Min John Tan, Mehul Motani
We explore a new perspective on adapting the learning rate (LR) schedule to improve the performance of the ReLU-based network as it is iteratively pruned.
no code implementations • 17 Oct 2021 • Shiyu Liu, Rohan Ghosh, Mehul Motani
In this paper, we propose a new forecasting strategy called Generative Forecasting (GenF), which generates synthetic data for the next few time steps and then makes long-range forecasts based on generated and observed data.
no code implementations • 20 Jul 2021 • Qingzhong Ai, Shiyu Liu, Lirong He, Zenglin Xu
In practice, we notice that the kernel used in SVGD-based methods has a decisive effect on the empirical performance.
1 code implementation • NeurIPS 2021 • Qingzhong Ai, Lirong He, Shiyu Liu, Zenglin Xu
To address this issue, we propose Bayesian Pseudocoresets Exemplar VAE (ByPE-VAE), a new variant of VAE with a prior based on Bayesian pseudocoreset.
1 code implementation • CVPR 2021 • Bowen Liu, Yu Chen, Shiyu Liu, Hun-Seok Kim
The proposed method first learns the efficient lower-dimensional latent space representation of each video frame and then performs inter-frame prediction in that latent domain.
no code implementations • 1 Jan 2021 • Shiyu Liu, Mehul Motani
Lastly, we conduct an ablation study to demonstrate the effectiveness of the cWGAN-GEP and the ITC algorithm.
no code implementations • 14 Nov 2019 • Shiyu Liu, Mehul Motani
Vital signs including heart rate, respiratory rate, body temperature and blood pressure, are critical in the clinical decision making process.
no code implementations • 2 Dec 2018 • Shiyu Liu, Mehul Motani
Feature selection, which searches for the most representative features in observed data, is critical for health data analysis.