Papers
Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity
Mario Bravo, Juan P. Flores-Mella, Cristóbal Guzmán
Neural Operators Can Play Dynamic Stackelberg Games
Guillermo A. Alvarez, Ibrahim Ekren, Anastasis Kratsios et al.
Reward-Directed Score-Based Diffusion Models via q-Learning
Xuefeng Gao, Jiale Zha, Xun Yu Zhou
Bayesian Score Calibration for Approximate Models
Joshua J. Bon, David J. Warne, David J. Nott et al.
Continuum Attention for Neural Operators
Edoardo Calvello, Nikola B. Kovachki, Matthew E. Levine et al.
Geometry-Dependent Matching Pursuit: a Transition Phase for Convergence on Linear Regression and LASSO
Celine Moucer, Adrien B. Taylor, Francis Bach
A statistical perspective on algorithm unrolling models for inverse problems
Yves Atchade, Xinru Liu, Qiuyun Zhu
Geodesic Slice Sampling on the Sphere
Michael Habeck, Mareike Hasenpflug, Shantanu Kodgirwar et al.
Kernel-based L_2-Boosting with Structure Constraints
Yao Wang, Xin Guo, Shao-Bo Lin
Global Convergence of Adjoint-Optimized Neural PDEs
Konstantin Riedl, Justin Sirignano, Konstantinos Spiliopoulos
Zono-Conformal Prediction: Zonotope-Based Uncertainty Quantification for Regression and Classification Tasks
Laura Lützow, Michael Eichelbeck, Mykel J. Kochenderfer et al.
Optimal Denoising in Score-Based Generative Models: The Role of Data Regularity
Eliot Beyler, Francis Bach
The Z-Gromov-Wasserstein Distance
Martin Bauer, Facundo Mémoli, Tom Needham et al.
Equivariant Manifold Neural ODEs and Differential Invariants
Emma Andersdotter, Daniel Persson, Fredrik Ohlsson
DeepCAVE: A Visualization and Analysis Tool for Automated Machine Learning
Sarah Segel, Helena Graf, Edward Bergman et al.
Proper losses regret at least 1/2-order
Han Bao, Asuka Takatsu
CAP: A General Algorithm for Online Selective Conformal Prediction with FCR Control
Yajie Bao, Yuyang Huo, Haojie Ren et al.
Client Selection for Federated Policy Optimization with Environment Heterogeneity
Zhijie Xie, Shenghui Song
Step and Smooth Decompositions as Topological Clustering
Luciano Vinas, Arash A. Amini
Nonlinear functional regression by functional deep neural network with kernel embedding
Zhongjie Shi, Jun Fan, Linhao Song et al.
Almost Sure Convergence of Dropout Algorithms for Neural Networks
Albert Senen--Cerda, Jaron Sanders
Geometric Operator Learning with Optimal Transport
Xinyi Li, Zongyi Li, Nikola Kovachki et al.
Backward Filtering Forward Guiding
Frank H. van der Meulen, S. Sommer
Optimal Decentralized Composite Optimization for Strongly Convex Functions
Haishan Ye, Xiangyu Chang