Papers
Large deviations rates for stochastic gradient descent with strongly convex functions
Dragana Bajovic, Dusan Jakovetic, Soummya Kar
Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games
Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto et al.
Learning Constrained Structured Spaces with Application to Multi-Graph Matching
Hedda Cohen Indelman, Tamir Hazan
Learning from Multiple Sources for Data-to-Text and Text-to-Data
Song Duong, Alberto Lumbreras, Mike Gartrell et al.
Learning in RKHM: a C*-Algebraic Twist for Kernel Machines
Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri
Learning k-qubit Quantum Operators via Pauli Decomposition
Mohsen Heidari, Wojciech Szpankowski
Learning Physics-Informed Neural Networks without Stacked Back-propagation
Di He, Shanda Li, Wenlei Shi et al.
Learning Robust Graph Neural Networks with Limited Supervision
Abdullah Alchihabi, Yuhong Guo
Learning Sparse Graphon Mean Field Games
Christian Fabian, Kai Cui, Heinz Koeppl
Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles
Rajeev Verma, Daniel Barrejon, Eric Nalisnick
Learning to Generalize Provably in Learning to Optimize
Junjie Yang, Tianlong Chen, Mingkang Zhu et al.
Learning to Optimize with Stochastic Dominance Constraints
Hanjun Dai, Yuan Xue, Niao He et al.
Learning Treatment Effects from Observational and Experimental Data
Sofia Triantafillou, Fattaneh Jabbari, Gregory F. Cooper
Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB
Zixian Yang, R. Srikant, Lei Ying
Learning with Partial Forgetting in Modern Hopfield Networks
Toshihiro Ota, Ikuro Sato, Rei Kawakami et al.
Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision
Jieyu Zhang, Linxin Song, Alex Ratner
Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation
Yaxuan Zhu, Jianwen Xie, Ping Li
Linear Convergence of Gradient Descent For Finite Width Over-parametrized Linear Networks With General Initialization
Ziqing Xu, Hancheng Min, Salma Tarmoun et al.
LOFT: Finding Lottery Tickets through Filter-wise Training
Qihan Wang, Chen Dun, Fangshuo Liao et al.
Loss-Curvature Matching for Dataset Selection and Condensation
Seungjae Shin, Heesun Bae, Donghyeok Shin et al.
Manifold Restricted Interventional Shapley Values
Muhammad Faaiz Taufiq, Patrick Blöbaum, Lenon Minorics
MARS: Masked Automatic Ranks Selection in Tensor Decompositions
Maxim Kodryan, Dmitry Kropotov, Dmitry Vetrov
Matching Map Recovery with an Unknown Number of Outliers
Arshak Minasyan, Tigran Galstyan, Sona Hunanyan et al.
Mean Parity Fair Regression in RKHS
Shaokui Wei, Jiayin Liu, Bing Li et al.
Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality
Ikko Yamane, Yann Chevaleyre, Takashi Ishida et al.