Papers
4,122 papers found
Recursive Quantile Estimation: Non-Asymptotic Confidence Bounds
Likai Chen, Georg Keilbar, Wei Biao Wu
Regularized Joint Mixture Models
Konstantinos Perrakis, Thomas Lartigue, Frank Dondelinger et al.
Reinforcement Learning for Joint Optimization of Multiple Rewards
Mridul Agarwal, Vaneet Aggarwal
Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD
Kun Yuan, Sulaiman A. Alghunaim, Xinmeng Huang
Reproducing Kernels and New Approaches in Compositional Data Analysis
Binglin Li, Changwon Yoon, Jeongyoun Ahn
Revisiting inference after prediction
Keshav Motwani, Daniela Witten
Revisiting minimum description length complexity in overparameterized models
Raaz Dwivedi, Chandan Singh, Bin Yu et al.
Ridges, Neural Networks, and the Radon Transform
Michael Unser
Risk Bounds for Positive-Unlabeled Learning Under the Selected At Random Assumption
Olivier Coudray, Christine Keribin, Pascal Massart et al.
Robust High-Dimensional Low-Rank Matrix Estimation: Optimal Rate and Data-Adaptive Tuning
Xiaolong Cui, Lei Shi, Wei Zhong et al.
Robust Load Balancing with Machine Learned Advice
Sara Ahmadian, Hossein Esfandiari, Vahab Mirrokni et al.
Robust Methods for High-Dimensional Linear Learning
Ibrahim Merad, Stéphane Gaïffas
RVCL: Evaluating the Robustness of Contrastive Learning via Verification
Zekai Wang, Weiwei Liu
Sample Complexity for Distributionally Robust Learning under chi-square divergence
Zhengyu Zhou, Weiwei Liu
Sampling random graph homomorphisms and applications to network data analysis
Hanbaek Lyu, Facundo Memoli, David Sivakoff
Scalable Computation of Causal Bounds
Madhumitha Shridharan, Garud Iyengar
Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance
Ray Bai, Mary R. Boland, Yong Chen
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice
Jonas Rothfuss, Martin Josifoski, Vincent Fortuin et al.
Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks
Khurram Javed, Haseeb Shah, Richard S. Sutton et al.
Scale Invariant Power Iteration
Cheolmin Kim, Youngseok Kim, Diego Klabjan
Scaling Up Models and Data with t5x and seqio
Adam Roberts, Hyung Won Chung, Gaurav Mishra et al.
Selection by Prediction with Conformal p-values
Ying Jin, Emmanuel J. Candes
Selective inference for k-means clustering
Yiqun T. Chen, Daniela M. Witten
Semiparametric Inference Using Fractional Posteriors
Alice L'Huillier, Luke Travis, Ismaël Castillo et al.