Papers
Benchmarking and Analyzing Point Cloud Classification under Corruptions
Jiawei Ren, Liang Pan, Ziwei Liu
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint
Hao Liu, Minshuo Chen, Siawpeng Er et al.
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features
Zhaowei Zhu, Jialu Wang, Yang Liu
Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity
Jingzhao Zhang, Hongzhou Lin, Subhro Das et al.
Biological Sequence Design with GFlowNets
Moksh Jain, Emmanuel Bengio, Alex Hernandez-Garcia et al.
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning
Philippe Hansen-Estruch, Amy Zhang, Ashvin Nair et al.
Bit Prioritization in Variational Autoencoders via Progressive Coding
Rui Shu, Stefano Ermon
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization
Jaehong Yoon, Geon Park, Wonyong Jeong et al.
Black-Box Tuning for Language-Model-as-a-Service
Tianxiang Sun, Yunfan Shao, Hong Qian et al.
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Junnan Li, Dongxu Li, Caiming Xiong et al.
Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning
Seyed Kamyar Seyed Ghasemipour, Satoshi Kataoka, Byron David et al.
Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness
Namuk Park, Songkuk Kim
Boosting Graph Structure Learning with Dummy Nodes
Xin Liu, Jiayang Cheng, Yangqiu Song et al.
Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization
Giuseppe Bruno De Luca, Eva Silverstein
Bounding the Width of Neural Networks via Coupled Initialization A Worst Case Analysis
Alexander Munteanu, Simon Omlor, Zhao Song et al.
Bounding Training Data Reconstruction in Private (Deep) Learning
Chuan Guo, Brian Karrer, Kamalika Chaudhuri et al.
Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understanding
Yifan Peng, Siddharth Dalmia, Ian Lane et al.
Branching Reinforcement Learning
Yihan Du, Wei Chen
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities
Julian Bitterwolf, Alexander Meinke, Maximilian Augustin et al.
Breaking the $\sqrtT$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits
Avishek Ghosh, Abishek Sankararaman
Bregman Neural Networks
Jordan Frecon, Gilles Gasso, Massimiliano Pontil et al.
Bregman Power k-Means for Clustering Exponential Family Data
Adithya Vellal, Saptarshi Chakraborty, Jason Q Xu
Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes
Tim Tsz-Kit Lau, Han Liu
Building Robust Ensembles via Margin Boosting
Dinghuai Zhang, Hongyang Zhang, Aaron Courville et al.