Papers
Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation
Zhihan Liu, Yufeng Zhang, Zuyue Fu et al.
Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos et al.
Learning Infinite-horizon Average-reward Markov Decision Process with Constraints
Liyu Chen, Rahul Jain, Haipeng Luo
Learning inverse folding from millions of predicted structures
Chloe Hsu, Robert Verkuil, Jason Liu et al.
Learning Iterative Reasoning through Energy Minimization
Yilun Du, Shuang Li, Joshua Tenenbaum et al.
Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits
Qinghua Liu, Yuanhao Wang, Chi Jin
Learning Mixtures of Linear Dynamical Systems
Yanxi Chen, H. Vincent Poor
Learning Multiscale Transformer Models for Sequence Generation
Bei Li, Tong Zheng, Yi Jing et al.
Learning of Cluster-based Feature Importance for Electronic Health Record Time-series
Henrique Aguiar, Mauro Santos, Peter Watkinson et al.
Learning Pseudometric-based Action Representations for Offline Reinforcement Learning
Pengjie Gu, Mengchen Zhao, Chen Chen et al.
Learning Stable Classifiers by Transferring Unstable Features
Yujia Bao, Shiyu Chang, Dr.Regina Barzilay
Learning Stochastic Shortest Path with Linear Function Approximation
Yifei Min, Jiafan He, Tianhao Wang et al.
Learning Symmetric Embeddings for Equivariant World Models
Jung Yeon Park, Ondrej Biza, Linfeng Zhao et al.
Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning
Max B Paulus, Giulia Zarpellon, Andreas Krause et al.
Learning to Estimate and Refine Fluid Motion with Physical Dynamics
Mingrui Zhang, Jianhong Wang, James B Tlhomole et al.
Learning to Hash Robustly, Guaranteed
Alexandr Andoni, Daniel Beaglehole
Learning to Incorporate Texture Saliency Adaptive Attention to Image Cartoonization
Xiang Gao, Yuqi Zhang, Yingjie Tian
Learning to Infer Structures of Network Games
Emanuele Rossi, Federico Monti, Yan Leng et al.
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters
Luc Brogat-Motte, Rémi Flamary, Celine Brouard et al.
Learning to Separate Voices by Spatial Regions
Alan Xu, Romit Roy Choudhury
Learning to Solve PDE-constrained Inverse Problems with Graph Networks
Qingqing Zhao, David B Lindell, Gordon Wetzstein
Least Squares Estimation using Sketched Data with Heteroskedastic Errors
Sokbae Lee, Serena Ng
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation
David Ireland, Giovanni Montana
Let Invariant Rationale Discovery Inspire Graph Contrastive Learning
Sihang Li, Xiang Wang, An Zhang et al.
Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time
David Woodruff, Amir Zandieh