Papers
Adversarial Teacher-Student Representation Learning for Domain Generalization
Fu-En Yang, Yuan-Chia Cheng, Zu-Yun Shiau et al.
Adversarial Training Helps Transfer Learning via Better Representations
Zhun Deng, Linjun Zhang, Kailas Vodrahalli et al.
A Faster Decentralized Algorithm for Nonconvex Minimax Problems
Wenhan Xian, Feihu Huang, Yanfu Zhang et al.
A Faster Maximum Cardinality Matching Algorithm with Applications in Machine Learning
Nathaniel Lahn, Sharath Raghvendra, Jiacheng Ye
AFEC: Active Forgetting of Negative Transfer in Continual Learning
Liyuan Wang, Mingtian Zhang, Zhongfan Jia et al.
A first-order primal-dual method with adaptivity to local smoothness
Maria-Luiza Vladarean, Yura Malitsky, Volkan Cevher
A flow-based latent state generative model of neural population responses to natural images
Mohammad Bashiri, Edgar Walker, Konstantin-Klemens Lurz et al.
A Framework to Learn with Interpretation
Jayneel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc
A Gang of Adversarial Bandits
Mark Herbster, Stephen Pasteris, Fabio Vitale et al.
A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning
Weishi Shi, Dayou Yu, Qi Yu
A generative nonparametric Bayesian model for whole genomes
Alan Amin, Eli N Weinstein, Debora Marks
Agent Modelling under Partial Observability for Deep Reinforcement Learning
Georgios Papoudakis, Filippos Christianos, Stefano Albrecht
A Geometric Analysis of Neural Collapse with Unconstrained Features
Zhihui Zhu, Tianyu Ding, Jinxin Zhou et al.
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition
Junjiao Tian, Dylan Yung, Yen-Chang Hsu et al.
A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast
Jongmin Lee, Chanwoo Park, Ernest Ryu
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations
Ayush Sekhari, Christoph Dann, Mehryar Mohri et al.
A Gradient Method for Multilevel Optimization
Ryo Sato, Mirai Tanaka, Akiko Takeda
A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems
Yi Ma, Xiaotian Hao, Jianye Hao et al.
A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression
Tobia Boschi, Matthew Reimherr, Francesca Chiaromonte
A Kernel-based Test of Independence for Cluster-correlated Data
Hongjiao Liu, Anna Plantinga, Yunhua Xiang et al.
A Law of Iterated Logarithm for Multi-Agent Reinforcement Learning
Gugan Chandrashekhar Thoppe, Bhumesh Kumar
Algorithmic Instabilities of Accelerated Gradient Descent
Amit Attia, Tomer Koren
Algorithmic stability and generalization of an unsupervised feature selection algorithm
xinxing wu, Qiang Cheng
Alias-Free Generative Adversarial Networks
Tero Karras, Miika Aittala, Samuli Laine et al.
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
Junnan Li, Ramprasaath Selvaraju, Akhilesh Gotmare et al.