Papers
4,122 papers found
Convergence for nonconvex ADMM, with applications to CT imaging
Rina Foygel Barber, Emil Y. Sidky
Convergence of Message-Passing Graph Neural Networks with Generic Aggregation on Large Random Graphs
Matthieu Cordonnier, Nicolas Keriven, Nicolas Tremblay et al.
Countering the Communication Bottleneck in Federated Learning: A Highly Efficient Zero-Order Optimization Technique
Elissa Mhanna, Mohamad Assaad
Critically Assessing the State of the Art in Neural Network Verification
Matthias König, Annelot W. Bosman, Holger H. Hoos et al.
DAG-Informed Structure Learning from Multi-Dimensional Point Processes
Chunming Zhang, Muhong Gao, Shengji Jia
Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls
Erich Kummerfeld, Jaewon Lim, Xu Shi
Data-Efficient Policy Evaluation Through Behavior Policy Search
Josiah P. Hanna, Yash Chandak, Philip S. Thomas et al.
Data Summarization via Bilevel Optimization
Zalán Borsos, Mojmír Mutný, Marco Tagliasacchi et al.
Data Thinning for Convolution-Closed Distributions
Anna Neufeld, Ameer Dharamshi, Lucy L. Gao et al.
Debiasing Evaluations That Are Biased by Evaluations
Jingyan Wang, Ivan Stelmakh, Yuting Wei et al.
Decentralized Natural Policy Gradient with Variance Reduction for Collaborative Multi-Agent Reinforcement Learning
Jinchi Chen, Jie Feng, Weiguo Gao et al.
Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics
Noga Mudrik, Yenho Chen, Eva Yezerets et al.
Decomposing Global Feature Effects Based on Feature Interactions
Julia Herbinger, Marvin N. Wright, Thomas Nagler et al.
Decorrelated Variable Importance
Isabella Verdinelli, Larry Wasserman
Deep Backward and Galerkin Methods for the Finite State Master Equation
Asaf Cohen, Mathieu Laurière, Ethan Zell
Deep Network Approximation: Beyond ReLU to Diverse Activation Functions
Shijun Zhang, Jianfeng Lu, Hongkai Zhao
Deep Neural Network Approximation of Invariant Functions through Dynamical Systems
Qianxiao Li, Ting Lin, Zuowei Shen
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces
Hao Liu, Haizhao Yang, Minshuo Chen et al.
Deep Nonparametric Quantile Regression under Covariate Shift
Xingdong Feng, Xin He, Yuling Jiao et al.
Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization
Cameron Jakub, Mihai Nica
Desiderata for Representation Learning: A Causal Perspective
Yixin Wang, Michael I. Jordan
Differentially Private Data Release for Mixed-type Data via Latent Factor Models
Yanqing Zhang, Qi Xu, Niansheng Tang et al.
Differentially private methods for managing model uncertainty in linear regression
Víctor Peña, Andrés F. Barrientos
Differentially Private Topological Data Analysis
Taegyu Kang, Sehwan Kim, Jinwon Sohn et al.