Papers
Boosted CVaR Classification
Runtian Zhai, Chen Dan, Arun Suggala et al.
Boosting with Multiple Sources
Corinna Cortes, Mehryar Mohri, Dmitry Storcheus et al.
Boost Neural Networks by Checkpoints
Feng Wang, Guoyizhe Wei, Qiao Liu et al.
Bootstrapping the Error of Oja's Algorithm
Robert Lunde, Purnamrita Sarkar, Rachel Ward
Bootstrap Your Object Detector via Mixed Training
Mengde Xu, Zheng Zhang, Fangyun Wei et al.
BooVAE: Boosting Approach for Continual Learning of VAE
Evgenii Egorov, Anna Kuzina, Evgeny Burnaev
BooVI: Provably Efficient Bootstrapped Value Iteration
Boyi Liu, Qi Cai, Zhuoran Yang et al.
Bounds all around: training energy-based models with bidirectional bounds
Cong Geng, Jia Wang, Zhiyong Gao et al.
Breaking the centralized barrier for cross-device federated learning
Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale et al.
Breaking the Dilemma of Medical Image-to-image Translation
Lingke Kong, Chenyu Lian, Detian Huang et al.
Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures
Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs
Han Zhong, Jiayi Huang, Lin Yang et al.
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning
Gen Li, Laixi Shi, Yuxin Chen et al.
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
Hyunsoo Chung, Jungtaek Kim, Boris Knyazev et al.
Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators
Qitian Wu, Rui Gao, Hongyuan Zha
Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection
NA DONG, Yongqiang Zhang, Mingli Ding et al.
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism
Paria Rashidinejad, Banghua Zhu, Cong Ma et al.
Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning
Nan Ding, Xi Chen, Tomer Levinboim et al.
Bridging the Imitation Gap by Adaptive Insubordination
Luca Weihs, Unnat Jain, Iou-Jen Liu et al.
Bubblewrap: Online tiling and real-time flow prediction on neural manifolds
Anne Draelos, Pranjal Gupta, Na Young Jun et al.
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining
Weizhe Hua, Yichi Zhang, Chuan Guo et al.
ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE
Qingzhong Ai, LIRONG HE, SHIYU LIU et al.
CAFE: Catastrophic Data Leakage in Vertical Federated Learning
Xiao Jin, Pin-Yu Chen, Chia-Yi Hsu et al.
Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration
Shengjia Zhao, Michael Kim, Roshni Sahoo et al.
Calibration and Consistency of Adversarial Surrogate Losses
Pranjal Awasthi, Natalie Frank, Anqi Mao et al.