Papers
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors
Karl Pertsch, Oleh Rybkin, Frederik Ebert et al.
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
Kaihua Tang, Jianqiang Huang, Hanwang Zhang
Look-ahead Meta Learning for Continual Learning
Gunshi Gupta, Karmesh Yadav, Liam Paull
LoopReg: Self-supervised Learning of Implicit Surface Correspondences, Pose and Shape for 3D Human Mesh Registration
Bharat Lal Bhatnagar, Cristian Sminchisescu, Christian Theobalt et al.
Low Distortion Block-Resampling with Spatially Stochastic Networks
Sarah Hong, Martin Arjovsky, Darryl Barnhart et al.
Lower Bounds and Optimal Algorithms for Personalized Federated Learning
Filip Hanzely, Slavomír Hanzely, Samuel Horváth et al.
Make One-Shot Video Object Segmentation Efficient Again
Tim Meinhardt, Laura Leal-Taixé
Making Non-Stochastic Control (Almost) as Easy as Stochastic
Max Simchowitz
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data
Kristopher Jensen, Ta-Chu Kao, Marco Tripodi et al.
Manifold structure in graph embeddings
Patrick Rubin-Delanchy
Marginal Utility for Planning in Continuous or Large Discrete Action Spaces
Zaheen Ahmad, Levi Lelis, Michael Bowling
Margins are Insufficient for Explaining Gradient Boosting
Allan Grønlund, Lior Kamma, Kasper Green Larsen
Markovian Score Climbing: Variational Inference with KL(p||q)
Christian Naesseth, Fredrik Lindsten, David M. Blei
MATE: Plugging in Model Awareness to Task Embedding for Meta Learning
Xiaohan Chen, Zhangyang Wang, Siyu Tang et al.
Matérn Gaussian Processes on Riemannian Manifolds
Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky et al.
Matrix Completion with Hierarchical Graph Side Information
Adel Elmahdy, Junhyung Ahn, Changho Suh et al.
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula
Yuxuan Zhao, Madeleine Udell
Matrix Inference and Estimation in Multi-Layer Models
Parthe Pandit, Mojtaba Sahraee Ardakan, Sundeep Rangan et al.
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
Long Zhao, Ting Liu, Xi Peng et al.
MCUNet: Tiny Deep Learning on IoT Devices
Ji Lin, Wei-Ming Chen, Yujun Lin et al.
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning
Elise van der Pol, Daniel Worrall, Herke van Hoof et al.
Measuring Robustness to Natural Distribution Shifts in Image Classification
Rohan Taori, Achal Dave, Vaishaal Shankar et al.
Measuring Systematic Generalization in Neural Proof Generation with Transformers
Nicolas Gontier, Koustuv Sinha, Siva Reddy et al.
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards
Yijie Guo, Jongwook Choi, Marcin Moczulski et al.
Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control
Giorgos ('Yorgos') Mamakoukas, Orest Xherija, Todd Murphey