Papers
11,951 papers found
Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks that Learn Features
Greg Yang, Michael Santacroce, Edward J Hu
Efficient decentralized multi-agent learning in asymmetric queuing systems
Daniel Freund, Thodoris Lykouris, Wentao Weng
Efficient Learning of Safe Driving Policy via Human-AI Copilot Optimization
Quanyi Li, Zhenghao Peng, Bolei Zhou
Efficiently Modeling Long Sequences with Structured State Spaces
Albert Gu, Karan Goel, Christopher Re
EfficientNeRF Efficient Neural Radiance Fields
Tao Hu, Shu Liu, Yilun Chen et al.
Efficient Neural Causal Discovery without Acyclicity Constraints
Phillip Lippe, Taco Cohen, Efstratios Gavves
Efficient Self-supervised Vision Transformers for Representation Learning
Chunyuan Li, Jianwei Yang, Pengchuan Zhang et al.
Efficient Sharpness-aware Minimization for Improved Training of Neural Networks
Jiawei Du, Hanshu Yan, Jiashi Feng et al.
Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization
Junyuan Hong, Haotao Wang, Zhangyang Wang et al.
Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators
John Guibas, Morteza Mardani, Zongyi Li et al.
Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums
Rui Pan, Haishan Ye, Tong Zhang
EigenGame Unloaded: When playing games is better than optimizing
Ian Gemp, Brian McWilliams, Claire Vernade et al.
Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation
Jun Xia, Ting Wang, Jiepin Ding et al.
Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise
Xingyu Wang, Sewoong Oh, Chang-Han Rhee
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling
Gianluigi Silvestri, Emily Fertig, Dave Moore et al.
Emergent Communication at Scale
Rahma Chaabouni, Florian Strub, Florent Altché et al.
Enabling Arbitrary Translation Objectives with Adaptive Tree Search
Wang Ling, Wojciech Stokowiec, Domenic Donato et al.
Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression
Bae Seong Park, Se Jung Kwon, Daehwan Oh et al.
End-to-End Learning of Probabilistic Hierarchies on Graphs
Daniel Zügner, Bertrand Charpentier, Morgane Ayle et al.
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning
Yatao Bian, Yu Rong, Tingyang Xu et al.
Energy-Inspired Molecular Conformation Optimization
Jiaqi Guan, Wesley Wei Qian, qiang liu et al.
Enhancing Cross-lingual Transfer by Manifold Mixup
Huiyun Yang, Huadong Chen, Hao Zhou et al.
EntQA: Entity Linking as Question Answering
Wenzheng Zhang, Wenyue Hua, Karl Stratos
Entroformer: A Transformer-based Entropy Model for Learned Image Compression
Yichen Qian, Xiuyu Sun, Ming Lin et al.