Papers
Local Augmentation for Graph Neural Networks
Songtao Liu, Rex Ying, Hanze Dong et al.
Local Linear Convergence of Douglas-Rachford for Linear Programming: a Probabilistic Analysis
Oisin Faust, Hamza Fawzi
Locally Sparse Neural Networks for Tabular Biomedical Data
Junchen Yang, Ofir Lindenbaum, Yuval Kluger
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets
Tal Shnitzer, Mikhail Yurochkin, Kristjan Greenewald et al.
Loss Function Learning for Domain Generalization by Implicit Gradient
Boyan Gao, Henry Gouk, Yongxin Yang et al.
Low-Complexity Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Multiplexed Parallel Convolutions
Eunsang Lee, Joon-Woo Lee, Junghyun Lee et al.
Low-Precision Stochastic Gradient Langevin Dynamics
Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa
LSB: Local Self-Balancing MCMC in Discrete Spaces
Emanuele Sansone
LyaNet: A Lyapunov Framework for Training Neural ODEs
Ivan Dario Jimenez Rodriguez, Aaron Ames, Yisong Yue
Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control
Katie Kang, Paula Gradu, Jason J Choi et al.
MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection
Zhenhong Sun, Ming Lin, Xiuyu Sun et al.
Making Linear MDPs Practical via Contrastive Representation Learning
Tianjun Zhang, Tongzheng Ren, Mengjiao Yang et al.
MAML and ANIL Provably Learn Representations
Liam Collins, Aryan Mokhtari, Sewoong Oh et al.
Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization
Hanjun Dai, Mengjiao Yang, Yuan Xue et al.
Marginal Tail-Adaptive Normalizing Flows
Mike Laszkiewicz, Johannes Lederer, Asja Fischer
Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems
Lukas Köhs, Bastian Alt, Heinz Koeppl
MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer
Jeewon Jeon, Woojun Kim, Whiyoung Jung et al.
Maslow’s Hammer in Catastrophic Forgetting: Node Re-Use vs. Node Activation
Sebastian Lee, Stefano Sarao Mannelli, Claudia Clopath et al.
Massively Parallel $k$-Means Clustering for Perturbation Resilient Instances
Vincent Cohen-Addad, Vahab Mirrokni, Peilin Zhong
Matching Learned Causal Effects of Neural Networks with Domain Priors
Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N Balasubramanian et al.
Matching Normalizing Flows and Probability Paths on Manifolds
Heli Ben-Hamu, Samuel Cohen, Joey Bose et al.
Matching Structure for Dual Learning
Hao Fei, Shengqiong Wu, Yafeng Ren et al.
Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching
Cheng Lu, Kaiwen Zheng, Fan Bao et al.
Meaningfully debugging model mistakes using conceptual counterfactual explanations
Abubakar Abid, Mert Yuksekgonul, James Zou
Measure Estimation in the Barycentric Coding Model
Matthew Werenski, Ruijie Jiang, Abiy Tasissa et al.