Papers
Greedy when Sure and Conservative when Uncertain about the Opponents
Haobo Fu, Ye Tian, Hongxiang Yu et al.
GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing
Zhongkai Hao, Chengyang Ying, Yinpeng Dong et al.
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation
Chris Dann, Yishay Mansour, Mehryar Mohri et al.
Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidance
Heeseung Kim, Sungwon Kim, Sungroh Yoon
Hardness and Algorithms for Robust and Sparse Optimization
Eric Price, Sandeep Silwal, Samson Zhou
H-Consistency Bounds for Surrogate Loss Minimizers
Pranjal Awasthi, Anqi Mao, Mehryar Mohri et al.
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning
Utku Evci, Vincent Dumoulin, Hugo Larochelle et al.
Hermite Polynomial Features for Private Data Generation
Margarita Vinaroz, Mohammad-Amin Charusaie, Frederik Harder et al.
Hessian-Free High-Resolution Nesterov Acceleration For Sampling
Ruilin Li, Hongyuan Zha, Molei Tao
Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models.
Abhineet Agarwal, Yan Shuo Tan, Omer Ronen et al.
Hindering Adversarial Attacks with Implicit Neural Representations
Andrei A Rusu, Dan Andrei Calian, Sven Gowal et al.
History Compression via Language Models in Reinforcement Learning
Fabian Paischer, Thomas Adler, Vihang Patil et al.
HousE: Knowledge Graph Embedding with Householder Parameterization
Rui Li, Jianan Zhao, Chaozhuo Li et al.
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models
Ahmed Alaa, Boris Van Breugel, Evgeny S. Saveliev et al.
How Powerful are Spectral Graph Neural Networks
Xiyuan Wang, Muhan Zhang
How Tempering Fixes Data Augmentation in Bayesian Neural Networks
Gregor Bachmann, Lorenzo Noci, Thomas Hofmann
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity
Chengyue Gong, Lemeng Wu, Qiang Liu
How to Leverage Unlabeled Data in Offline Reinforcement Learning
Tianhe Yu, Aviral Kumar, Yevgen Chebotar et al.
How to Stay Curious while avoiding Noisy TVs using Aleatoric Uncertainty Estimation
Augustine Mavor-Parker, Kimberly Young, Caswell Barry et al.
How to Steer Your Adversary: Targeted and Efficient Model Stealing Defenses with Gradient Redirection
Mantas Mazeika, Bo Li, David Forsyth
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective
Akhilan Boopathy, Ila Fiete
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation
Xiaoyu Chen, Han Zhong, Zhuoran Yang et al.
HyperImpute: Generalized Iterative Imputation with Automatic Model Selection
Daniel Jarrett, Bogdan C Cebere, Tennison Liu et al.
HyperPrompt: Prompt-based Task-Conditioning of Transformers
Yun He, Steven Zheng, Yi Tay et al.