Papers
4,122 papers found
Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning
Titouan Vayer, Rémi Gribonval
Convergence Rates of a Class of Multivariate Density Estimation Methods Based on Adaptive Partitioning
Linxi Liu, Dangna Li, Wing Hung Wong
Convex Reinforcement Learning in Finite Trials
Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis et al.
DART: Distance Assisted Recursive Testing
Xuechan Li, Anthony D. Sung, Jichun Xie
Decentralized Learning: Theoretical Optimality and Practical Improvements
Yucheng Lu, Christopher De Sa
Decentralized Robust V-learning for Solving Markov Games with Model Uncertainty
Shaocong Ma, Ziyi Chen, Shaofeng Zou et al.
Deep linear networks can benignly overfit when shallow ones do
Niladri S. Chatterji, Philip M. Long
Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility
Hoil Lee, Fadhel Ayed, Paul Jung et al.
Deletion and Insertion Tests in Regression Models
Naofumi Hama, Masayoshi Mase, Art B. Owen
Densely Connected G-invariant Deep Neural Networks with Signed Permutation Representations
Devanshu Agrawal, James Ostrowski
Density estimation on low-dimensional manifolds: an inflation-deflation approach
Christian Horvat, Jean-Pascal Pfister
Differentially Private Hypothesis Testing for Linear Regression
Daniel G. Alabi, Salil P. Vadhan
Dimensionality Reduction and Wasserstein Stability for Kernel Regression
Stephan Eckstein, Armin Iske, Mathias Trabs
Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data
Yuqi Gu, Elena E. Erosheva, Gongjun Xu et al.
Dimensionless machine learning: Imposing exact units equivariance
Soledad Villar, Weichi Yao, David W. Hogg et al.
Dimension Reduction and MARS
Yu Liu LIU, Degui Li, Yingcun Xia
Dimension Reduction in Contextual Online Learning via Nonparametric Variable Selection
Wenhao Li, Ningyuan Chen, L. Jeff Hong
Discovering Salient Neurons in deep NLP models
Nadir Durrani, Fahim Dalvi, Hassan Sajjad
Discrete Variational Calculus for Accelerated Optimization
Cédric M. Campos, Alejandro Mahillo, David Martín de Diego
Distinguishing Cause and Effect in Bivariate Structural Causal Models: A Systematic Investigation
Christoph Käding, Jakob Runge
Distributed Algorithms for U-statistics-based Empirical Risk Minimization
Lanjue Chen, Alan T.K. Wan, Shuyi Zhang et al.
Distributed Community Detection in Large Networks
Sheng Zhang, Rui Song, Wenbin Lu et al.
Distributed Nonparametric Regression Imputation for Missing Response Problems with Large-scale Data
Ruoyu Wang, Miaomiao Su, Qihua Wang
Distributed Sparse Regression via Penalization
Yao Ji, Gesualdo Scutari, Ying Sun et al.