Papers
A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equation
Shu Liu, Stanley Osher, Wuchen Li
Generalized Resubstitution for Regression Error Estimation
Diego Marcondes, Ulisses Braga-Neto
Transfer Conformal Predictive Inference for Regression
Ce Zhang, Ting Li, Jinhan Xie et al.
Towards Convexity in Anomaly Detection: A New Formulation of SSLM with Unique Optimal Solutions
Hongying Liu, Hao Wang, Haoran Chu et al.
Node Regression on Latent Position Random Graphs via Local Averaging
Martin Gjorgjevski, Nicolas Keriven, Simon Barthelme et al.
On the Relevance of Byzantine Robust Optimization Against Data Poisoning
Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta et al.
Best Arm Identification with Minimal Regret
Junwen Yang, Vincent Y. F. Tan, Tianyuan Jin
Convergence of Noise-Free Sampling Algorithms with Regularized Wasserstein Proximals
Fuqun Han, Stanley Osher, Wuchen Li
Almost Sure Convergence of Linear Temporal Difference Learning with Arbitrary Features
Jiuqi Wang, Shangtong Zhang
Asymptotics of Stochastic Gradient Descent with Dropout Regularization in Linear Models
Jiaqi Li, Johannes Schmidt-Hieber, Wei Biao Wu
Beyond Unconstrained Features: Neural Collapse for Shallow Neural Networks with General Data
Wanli Hong, Shuyang Ling
Differentially Private Estimation and Inference in High-Dimensional Regression with FDR Control
Zhanrui Cai, Sai Li, Xintao Xia et al.
Demographic Parity in Regression and Classification Within the Unawareness Framework
Vincent Divol, Solenne Gaucher
Enhancing Accuracy in Generative Models via Knowledge Transfer
Xinyu Tian, Xiaotong Shen
Multi-relational Network Autoregression Model with Latent Group Structures
Yimeng Ren, Xuening Zhu, Ganggang Xu et al.
Limiting Over-Smoothing and Over-Squashing of Graph Message Passing by Deep Scattering Transforms
Yuanhong Jiang, Dongmian Zou, Xiaoqun Zhang et al.
A Fully Parameter-Free Second-Order Algorithm for Convex-Concave Minimax Problems
Jun-Lin Wang, Zi Xu, Hui-Ling Zhang
Stochastic Differential Equations models for Least-Squares Stochastic Gradient Descent
Adrien Schertzer, Loucas Pillaud-Vivien
Vector-Valued Gaussian Processes for Approximating Divergence- or Rotation-free Vector Fields
Quoc Thong Le Gia, Ian Hugh Sloan, Holger Wendland
Differentially Private Best-Arm Identification
Achraf Azize, Marc Jourdan, Aymen Al Marjani et al.
Corruptions of Supervised Learning Problems: Typology and Mitigations
Laura Iacovissi, Nan Lu, Robert C. Williamson
Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies
Sébastien Lachapelle, Pau Rodríguez López, Yash Sharma et al.
A Mean-Field Analysis of Neural Stochastic Gradient Descent-Ascent for Functional Minimax Optimization
Yuchen Zhu, Yufeng Zhang, Zhaoran Wang et al.
Minimax density estimation in the adversarial framework under local differential privacy
Mélisande Albert, Juliette Chevallier, Béatrice Laurent et al.
Approximations and Learning for Continuous State and Action MDPs under Average Cost Criteria
Ali D. Kara, Serdar Yüksel