Papers
RelaySum for Decentralized Deep Learning on Heterogeneous Data
Thijs Vogels, Lie He, Anastasiia Koloskova et al.
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection
Chunjong Park, Anas Awadalla, Tadayoshi Kohno et al.
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions
Ignavier Ng, Yujia Zheng, Jiji Zhang et al.
Reliable Decisions with Threshold Calibration
Roshni Sahoo, Shengjia Zhao, Alyssa Chen et al.
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space
Sandesh Ghimire, Aria Masoomi, Jennifer Dy
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability
Dylan Slack, Anna Hilgard, Sameer Singh et al.
ReLU Regression with Massart Noise
Ilias Diakonikolas, Jong Ho Park, Christos Tzamos
Remember What You Want to Forget: Algorithms for Machine Unlearning
Ayush Sekhari, Jayadev Acharya, Gautam Kamath et al.
REMIPS: Physically Consistent 3D Reconstruction of Multiple Interacting People under Weak Supervision
Mihai Fieraru, Mihai Zanfir, Teodor Szente et al.
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience
Dominic Gonschorek, Larissa Höfling, Klaudia P. Szatko et al.
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning
Antonious Girgis, Deepesh Data, Suhas Diggavi
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification
Ben Eysenbach, Sergey Levine, Ruslan Salakhutdinov
Replay-Guided Adversarial Environment Design
Minqi Jiang, Michael Dennis, Jack Parker-Holder et al.
Representation Costs of Linear Neural Networks: Analysis and Design
Zhen Dai, Mina Karzand, Nathan Srebro
Representation Learning Beyond Linear Prediction Functions
Ziping Xu, Ambuj Tewari
Representation Learning for Event-based Visuomotor Policies
Sai Vemprala, Sami Mian, Ashish Kapoor
Representation Learning on Spatial Networks
Zheng Zhang, Liang Zhao
Representing Hyperbolic Space Accurately using Multi-Component Floats
Tao Yu, Christopher M De Sa
Representing Long-Range Context for Graph Neural Networks with Global Attention
Zhanghao Wu, Paras Jain, Matthew Wright et al.
Repulsive Deep Ensembles are Bayesian
Francesco D'Angelo, Vincent Fortuin
Re-ranking for image retrieval and transductive few-shot classification
Xi SHEN, Yang Xiao, Shell Xu Hu et al.
Residual2Vec: Debiasing graph embedding with random graphs
Sadamori Kojaku, Jisung Yoon, Isabel Constantino et al.
Residual Pathway Priors for Soft Equivariance Constraints
Marc Finzi, Gregory Benton, Andrew G Wilson
Residual Relaxation for Multi-view Representation Learning
Yifei Wang, Zhengyang Geng, Feng Jiang et al.