1.6k citations · 7.3k across the 231 of their papers we have counts for
59 papers · 1 filter
Search Behavior Prediction: A Hypergraph Perspective
Yan Han, Edward W Huang, Wenqing Zheng +3
Although the bipartite shopping graphs are straightforward to model search behavior, they suffer from two challenges: 1) The majority of items are sporadically searched and hence h…
Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training
Zhenglun Kong, Haoyu Ma, Geng Yuan +12
Vision transformers (ViTs) have recently obtained success in many applications, but their intensive computation and heavy memory usage at both training and inference time limit the…
QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks
Kaixiong Zhou, Zhenyu Zhang, Shengyuan Chen +4
Quantum neural networks (QNNs), an interdisciplinary field of quantum computing and machine learning, have attracted tremendous research interests due to the specific quantum advan…
Scaling Multimodal Pre-Training via Cross-Modality Gradient Harmonization
Junru Wu, Yi Liang, Feng Han +3
Self-supervised pre-training recently demonstrates success on large-scale multimodal data, and state-of-the-art contrastive learning methods often enforce the feature consistency f…
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets
Tianjin Huang, Tianlong Chen, Meng Fang +8
Recent works have impressively demonstrated that there exists a subnetwork in randomly initialized convolutional neural networks (CNNs) that can match the performance of the fully…
Efficient Image Generation with Variadic Attention Heads
Steven Walton, Ali Hassani, Xingqian Xu +2
While the integration of transformers in vision models have yielded significant improvements on vision tasks they still require significant amounts of computation for both training…