Papers
Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning
Angelo Damiani, Giorgio Manganini, Alberto Maria Metelli et al.
BAMDT: Bayesian Additive Semi-Multivariate Decision Trees for Nonparametric Regression
Zhao Tang Luo, Huiyan Sang, Bani Mallick
Batched Dueling Bandits
Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan
Batch Greenkhorn Algorithm for Entropic-Regularized Multimarginal Optimal Transport: Linear Rate of Convergence and Iteration Complexity
Vladimir R. Kostic, Saverio Salzo, Massimiliano Pontil
Bayesian Continuous-Time Tucker Decomposition
Shikai Fang, Akil Narayan, Robert Kirby et al.
Bayesian Deep Embedding Topic Meta-Learner
Zhibin Duan, Yishi Xu, Jianqiao Sun et al.
Bayesian Imitation Learning for End-to-End Mobile Manipulation
Yuqing Du, Daniel Ho, Alex Alemi et al.
Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial Defense
Bao Gia Doan, Ehsan M. Abbasnejad, Javen Qinfeng Shi et al.
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Sanae Lotfi, Pavel Izmailov, Gregory Benton et al.
Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations
Fan Yin, Jieying Jiao, Jun Yan et al.
Bayesian Nonparametrics for Offline Skill Discovery
Valentin Villecroze, Harry Braviner, Panteha Naderian et al.
Bayesian Optimization for Distributionally Robust Chance-constrained Problem
Yu Inatsu, Shion Takeno, Masayuki Karasuyama et al.
Bayesian Optimization under Stochastic Delayed Feedback
Arun Verma, Zhongxiang Dai, Bryan Kian Hsiang Low
Being Properly Improper
Tyler Sypherd, Richard Nock, Lalitha Sankar
Be Like Water: Adaptive Floating Point for Machine Learning
Thomas Yeh, Max Sterner, Zerlina Lai et al.
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.