Papers
11,015 papers found
Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash
Backdoor Defense via Decoupling the Training Process
Kunzhe Huang, Yiming Li, Baoyuan Wu et al.
BadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models
Kangjie Chen, Yuxian Meng, Xiaofei Sun et al.
Bag of Instances Aggregation Boosts Self-supervised Distillation
Haohang Xu, Jiemin Fang, XIAOPENG ZHANG et al.
BAM: Bayes with Adaptive Memory
Josue Nassar, Jennifer Rogers Brennan, Ben Evans et al.
Bandit Learning with Joint Effect of Incentivized Sampling, Delayed Sampling Feedback, and Self-Reinforcing User Preferences
Tianchen Zhou, Jia Liu, Chaosheng Dong et al.
Bayesian Framework for Gradient Leakage
Mislav Balunovic, Dimitar Iliev Dimitrov, Robin Staab et al.
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How
Yuning You, Yue Cao, Tianlong Chen et al.
Bayesian Neural Network Priors Revisited
Vincent Fortuin, Adrià Garriga-Alonso, Sebastian W. Ober et al.
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis
Max W. Y. Lam, Jun Wang, Dan Su et al.
BEiT: BERT Pre-Training of Image Transformers
Hangbo Bao, Li Dong, Songhao Piao et al.
Benchmarking the Spectrum of Agent Capabilities
Danijar Hafner
Better Supervisory Signals by Observing Learning Paths
Yi Ren, Shangmin Guo, Danica J. Sutherland
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains
Qilong Zhang, Xiaodan Li, YueFeng Chen et al.
BiBERT: Accurate Fully Binarized BERT
Haotong Qin, Yifu Ding, Mingyuan Zhang et al.
Bi-linear Value Networks for Multi-goal Reinforcement Learning
Zhang-Wei Hong, Ge Yang, Pulkit Agrawal
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions
Juncheng Dong, Simiao Ren, Yang Deng et al.
Boosted Curriculum Reinforcement Learning
Pascal Klink, Carlo D'Eramo, Jan Peters et al.
Boosting Randomized Smoothing with Variance Reduced Classifiers
Miklós Z. Horváth, Mark Niklas Mueller, Marc Fischer et al.
Boosting the Certified Robustness of L-infinity Distance Nets
Bohang Zhang, Du Jiang, Di He et al.
Bootstrapped Meta-Learning
Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy et al.
Bootstrapping Semantic Segmentation with Regional Contrast
Shikun Liu, Shuaifeng Zhi, Edward Johns et al.
Bregman Gradient Policy Optimization
Feihu Huang, Shangqian Gao, Heng Huang
Bridging Recommendation and Marketing via Recurrent Intensity Modeling
Yifei Ma, Ge Liu, Anoop Deoras
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations
Sarath Sreedharan, Utkarsh Soni, Mudit Verma et al.