Papers
Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences
Aadirupa Saha, Pierre Gaillard
Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching
Yecheng Ma, Andrew Shen, Dinesh Jayaraman et al.
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
Zhenheng Tang, Yonggang Zhang, Shaohuai Shi et al.
Visual Attention Emerges from Recurrent Sparse Reconstruction
Baifeng Shi, Yale Song, Neel Joshi et al.
ViT-NeT: Interpretable Vision Transformers with Neural Tree Decoder
Sangwon Kim, Jaeyeal Nam, Byoung Chul Ko
VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix
Teng Wang, Wenhao Jiang, Zhichao Lu et al.
VLUE: A Multi-Task Multi-Dimension Benchmark for Evaluating Vision-Language Pre-training
Wangchunshu Zhou, Yan Zeng, Shizhe Diao et al.
Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes
Gregory Benton, Wesley Maddox, Andrew Gordon Wilson
Weisfeiler-Lehman Meets Gromov-Wasserstein
Samantha Chen, Sunhyuk Lim, Facundo Memoli et al.
Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy
Zhihan Liu, Miao Lu, Zhaoran Wang et al.
What Can Linear Interpolation of Neural Network Loss Landscapes Tell Us?
Tiffany J Vlaar, Jonathan Frankle
What Dense Graph Do You Need for Self-Attention?
Yuxin Wang, Chu-Tak Lee, Qipeng Guo et al.
What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization?
Thomas Wang, Adam Roberts, Daniel Hesslow et al.
When and How Mixup Improves Calibration
Linjun Zhang, Zhun Deng, Kenji Kawaguchi et al.
When Are Linear Stochastic Bandits Attackable?
Huazheng Wang, Haifeng Xu, Hongning Wang
When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee
Dixian Zhu, Gang Li, Bokun Wang et al.
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error
Scott Fujimoto, David Meger, Doina Precup et al.
Why the Rich Get Richer? On the Balancedness of Random Partition Models
Changwoo J Lee, Huiyan Sang
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling
Jiri Hron, Roman Novak, Jeffrey Pennington et al.
Wide Neural Networks Forget Less Catastrophically
Seyed Iman Mirzadeh, Arslan Chaudhry, Dong Yin et al.
Winning the Lottery Ahead of Time: Efficient Early Network Pruning
John Rachwan, Daniel Zügner, Bertrand Charpentier et al.
XAI for Transformers: Better Explanations through Conservative Propagation
Ameen Ali, Thomas Schnake, Oliver Eberle et al.
You Only Cut Once: Boosting Data Augmentation with a Single Cut
Junlin Han, Pengfei Fang, Weihao Li et al.
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for Everyone
Edresson Casanova, Julian Weber, Christopher D Shulby et al.
Zero-shot AutoML with Pretrained Models
Ekrem Öztürk, Fabio Ferreira, Hadi Jomaa et al.