Papers
11,951 papers found
Exploring Balanced Feature Spaces for Representation Learning
Bingyi Kang, Yu Li, Sa Xie et al.
Exploring the Uncertainty Properties of Neural Networks’ Implicit Priors in the Infinite-Width Limit
Ben Adlam, Jaehoon Lee, Lechao Xiao et al.
Expressive Power of Invariant and Equivariant Graph Neural Networks
Waiss Azizian, marc lelarge
Extracting Strong Policies for Robotics Tasks from Zero-Order Trajectory Optimizers
Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes et al.
Extreme Memorization via Scale of Initialization
Harsh Mehta, Ashok Cutkosky, Behnam Neyshabur
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments
Anirudh Goyal, Alex Lamb, Phanideep Gampa et al.
FairBatch: Batch Selection for Model Fairness
Yuji Roh, Kangwook Lee, Steven Euijong Whang et al.
FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders
Pengyu Cheng, Weituo Hao, Siyang Yuan et al.
Fair Mixup: Fairness via Interpolation
Ching-Yao Chuang, Youssef Mroueh
Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers
Sahil Singla, Soheil Feizi
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers
Kaidi Xu, Huan Zhang, Shiqi Wang et al.
Fast And Slow Learning Of Recurrent Independent Mechanisms
Kanika Madan, Nan Rosemary Ke, Anirudh Goyal et al.
Fast convergence of stochastic subgradient method under interpolation
Huang Fang, Zhenan Fan, Michael Friedlander
Faster Binary Embeddings for Preserving Euclidean Distances
Jinjie Zhang, Rayan Saab
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling
Difan Zou, Pan Xu, Quanquan Gu
Fast Geometric Projections for Local Robustness Certification
Aymeric Fromherz, Klas Leino, Matt Fredrikson et al.
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
Yi Ren, Chenxu Hu, Xu Tan et al.
Fast Training Method for Stochastic Compositional Optimization Problems
Hongchang Gao, Heng Huang
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning
Hong-You Chen, Wei-Lun Chao
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
Xiaoxiao Li, Meirui JIANG, Xiaofei Zhang et al.
Federated Learning Based on Dynamic Regularization
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas et al.
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms
Maruan Al-Shedivat, Jennifer Gillenwater, Eric Xing et al.
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning
Wonyong Jeong, Jaehong Yoon, Eunho Yang et al.
Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis
Sangjoon Park, Gwanghyun Kim, Jeongsol Kim et al.
FedMix: Approximation of Mixup under Mean Augmented Federated Learning
Tehrim Yoon, Sumin Shin, Sung Ju Hwang et al.