6 citations · 14 across the 7 of their papers we have counts for
8 papers
Robust Graph Structure Learning with the Alignment of Features and Adjacency Matrix
Shaogao Lv, Gang Wen, Shiyu Liu +2
To improve the robustness of graph neural networks (GNN), graph structure learning (GSL) has attracted great interest due to the pervasiveness of noise in graph data. Many approach…
Stability and Generalization of lp-Regularized Stochastic Learning for GCN
Shiyu Liu, Linsen Wei, Shaogao Lv +1
Graph convolutional networks (GCN) are viewed as one of the most popular representations among the variants of graph neural networks over graph data and have shown powerful perform…
StoCFL: A Stochastically Clustered Federated Learning Framework for Non-IID Data with Dynamic Client Participation
Dun Zeng, Xiangjing Hu, Shiyu Liu +3
Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices. In real-world federated learning systems, these data…
Towards Better Long-range Time Series Forecasting using Generative Forecasting
Shiyu Liu, Rohan Ghosh, Mehul Motani
Long-range time series forecasting is usually based on one of two existing forecasting strategies: Direct Forecasting and Iterative Forecasting, where the former provides low bias,…
S-Cyc: A Learning Rate Schedule for Iterative Pruning of ReLU-based Networks
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. Our work and contribution…
Towards Better Long-range Time Series Forecasting using Generative Adversarial Networks
Shiyu Liu, Rohan Ghosh, Mehul Motani
Long-range time series forecasting is usually based on one of two existing forecasting strategies: Direct Forecasting and Iterative Forecasting, where the former provides low bias,…
Stein Variational Gradient Descent with Multiple Kernel
Qingzhong Ai, Shiyu Liu, Lirong He +1
Stein variational gradient descent (SVGD) and its variants have shown promising successes in approximate inference for complex distributions. In practice, we notice that the kernel…
ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE
Qingzhong Ai, Lirong He, Shiyu Liu +1
Recent studies show that advanced priors play a major role in deep generative models. Exemplar VAE, as a variant of VAE with an exemplar-based prior, has achieved impressive result…