Papers
4,122 papers found
Step and Smooth Decompositions as Topological Clustering
Luciano Vinas, Arash A. Amini
Stochastic Interior-Point Methods for Smooth Conic Optimization with Applications
Chuan He, Zhanwang Deng
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
Michael Albergo, Nicholas M. Boffi, Eric Vanden-Eijnden
Substitute Adjustment via Recovery of Latent Variables
Jeffrey Adams, Niels Richard Hansen
Supervised Learning with Evolving Tasks and Performance Guarantees
Verónica Álvarez, Santiago Mazuelas, Jose A. Lozano
System Neural Diversity: Measuring Behavioral Heterogeneity in Multi-Agent Learning
Matteo Bettini, Ajay Shankar, Amanda Prorok
Talent: A Tabular Analytics and Learning Toolbox
Si-Yang Liu, Hao-Run Cai, Qi-Le Zhou et al.
Test-Time Training on Video Streams
Renhao Wang, Yu Sun, Arnuv Tandon et al.
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
Jiin Woo, Gauri Joshi, Yuejie Chi
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning
Nikhil Ghosh, Spencer Frei, Wooseok Ha et al.
The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs
Peter Mostowsky, Vincent Dutordoir, Iskander Azangulov et al.
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
Shuze Daniel Liu, Shuhang Chen, Shangtong Zhang
The Z-Gromov-Wasserstein Distance
Martin Bauer, Facundo Mémoli, Tom Needham et al.
TorchCP: A Python Library for Conformal Prediction
Jianguo Huang, Jianqing Song, Xuanning Zhou et al.
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification
Brendon G. Anderson, Ziye Ma, Jingqi Li et al.
Towards Understanding Gradient Flow Dynamics of Homogeneous Neural Networks Beyond the Origin
Akshay Kumar, Jarvis Haupt
Towards Unified Native Spaces in Kernel Methods
Xavier Emery, Emilio Porcu, Moreno Bevilacqua
Transformers from Diffusion: A Unified Framework for Neural Message Passing
Qitian Wu, David Wipf, Junchi Yan
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
Tianyi Lin, Chi Jin, Michael I. Jordan
Unbalanced Kantorovich-Rubinstein distance, plan, and barycenter on nite spaces: A statistical perspective
Shayan Hundrieser, Florian Heinemann, Marcel Klatt et al.
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination
Peng Wang, Xiao Li, Can Yaras et al.
Unified Discrete Diffusion for Categorical Data
Lingxiao Zhao, Xueying Ding, Lijun Yu et al.
Universality of Kernel Random Matrices and Kernel Regression in the Quadratic Regime
Parthe Pandit, Zhichao Wang, Yizhe Zhu
Universal Online Convex Optimization Meets Second-order Bounds
Lijun Zhang, Yibo Wang, Guanghui Wang et al.
Uplift Model Evaluation with Ordinal Dominance Graphs
Brecht Verbeken, Marie-Anne Guerry, Wouter Verbeke et al.