Papers
When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations
Chunhui Zhang, Chao Huang, Yijun Tian et al.
Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression
Yihao Xue, Siddharth Joshi, Eric Gan et al.
Which Invariance Should We Transfer? A Causal Minimax Learning Approach
Mingzhou Liu, Xiangyu Zheng, Xinwei Sun et al.
Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?
Yu Yao, Mingming Gong, Yuxuan Du et al.
Which Tricks are Important for Learning to Rank?
Ivan Lyzhin, Aleksei Ustimenko, Andrey Gulin et al.
Who Needs to Know? Minimal Knowledge for Optimal Coordination
Niklas Lauffer, Ameesh Shah, Micah Carroll et al.
Whose Opinions Do Language Models Reflect?
Shibani Santurkar, Esin Durmus, Faisal Ladhak et al.
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts
Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi et al.
Why does Throwing Away Data Improve Worst-Group Error?
Kamalika Chaudhuri, Kartik Ahuja, Martin Arjovsky et al.
Why do Nearest Neighbor Language Models Work?
Frank F. Xu, Uri Alon, Graham Neubig
Why Is Public Pretraining Necessary for Private Model Training?
Arun Ganesh, Mahdi Haghifam, Milad Nasr et al.
Why Random Pruning Is All We Need to Start Sparse
Advait Harshal Gadhikar, Sohom Mukherjee, Rebekka Burkholz
Why Target Networks Stabilise Temporal Difference Methods
Mattie Fellows, Matthew J. A. Smith, Shimon Whiteson
Width and Depth Limits Commute in Residual Networks
Soufiane Hayou, Greg Yang
WL meet VC
Christopher Morris, Floris Geerts, Jan Tönshoff et al.
X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion
Hanqing Zhao, Dianmo Sheng, Jianmin Bao et al.
XTab: Cross-table Pretraining for Tabular Transformers
Bingzhao Zhu, Xingjian Shi, Nick Erickson et al.
$p$-Laplacian Based Graph Neural Networks
Guoji Fu, Peilin Zhao, Yatao Bian
3D Infomax improves GNNs for Molecular Property Prediction
Hannes Stärk, Dominique Beaini, Gabriele Corso et al.
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design
Yinan Huang, Xingang Peng, Jianzhu Ma et al.
3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation
Peter Richtarik, Igor Sokolov, Elnur Gasanov et al.
A$^3$T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and Editing
He Bai, Renjie Zheng, Junkun Chen et al.
A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks
Huan Zhang, Shiqi Wang, Kaidi Xu et al.
Accelerated Federated Learning with Decoupled Adaptive Optimization
Jiayin Jin, Jiaxiang Ren, Yang Zhou et al.