Papers
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.
Zero-Shot Reward Specification via Grounded Natural Language
Parsa Mahmoudieh, Deepak Pathak, Trevor Darrell
12-Lead ECG Reconstruction via Koopman Operators
Tomer Golany, Kira Radinsky, Daniel Freedman et al.
1-bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan et al.
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Zehao Xiao, Jiayi Shen, Xiantong Zhen et al.
Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework
Wenxiao Wang, Minghao Chen, Shuai Zhao et al.
Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving
Yang Song, Chenlin Meng, Renjie Liao et al.
Accelerating Gossip SGD with Periodic Global Averaging
Yiming Chen, Kun Yuan, Yingya Zhang et al.
Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan et al.
Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
Accumulated Decoupled Learning with Gradient Staleness Mitigation for Convolutional Neural Networks
Huiping Zhuang, Zhenyu Weng, Fulin Luo et al.
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu et al.
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
John P Miller, Rohan Taori, Aditi Raghunathan et al.
Accurate Post Training Quantization With Small Calibration Sets
Itay Hubara, Yury Nahshan, Yair Hanani et al.
ACE: Explaining cluster from an adversarial perspective
Yang Young Lu, Timothy C Yu, Giancarlo Bonora et al.