Papers
Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation
Zekang Zhang, Guangyu Gao, Zhiyuan Fang et al.
MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Training
De-An Huang, Zhiding Yu, Anima Anandkumar
Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently
Haoyuan Sun, Kwangjun Ahn, Christos Thrampoulidis et al.
Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM
Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL
Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine et al.
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models
Erdun Gao, Ignavier Ng, Mingming Gong et al.
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo
Ignacio Peis, Chao Ma, José Miguel Hernández-Lobato
Misspecified Phase Retrieval with Generative Priors
Zhaoqiang Liu, Xinshao Wang, Jiulong Liu
Mix and Reason: Reasoning over Semantic Topology with Data Mixing for Domain Generalization
Chaoqi Chen, Luyao Tang, Feng Liu et al.
Mixture-of-Experts with Expert Choice Routing
Yanqi Zhou, Tao Lei, Hanxiao Liu et al.
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri et al.
MoCoDA: Model-based Counterfactual Data Augmentation
Silviu Pitis, Elliot Creager, Ajay Mandlekar et al.
Model-Based Imitation Learning for Urban Driving
Anthony Hu, Gianluca Corrado, Nicolas Griffiths et al.
Model-based Lifelong Reinforcement Learning with Bayesian Exploration
Haotian Fu, Shangqun Yu, Michael L. Littman et al.
Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief
Kaiyang Guo, Shao Yunfeng, Yanhui Geng
Model-Based Opponent Modeling
XiaoPeng Yu, Jiechuan Jiang, Wanpeng Zhang et al.
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity
Alekh Agarwal, Tong Zhang
Model-based Safe Deep Reinforcement Learning via a Constrained Proximal Policy Optimization Algorithm
Ashish K Jayant, Shalabh Bhatnagar
Modeling Human Exploration Through Resource-Rational Reinforcement Learning
Marcel Binz, Eric Schulz
Modeling the Machine Learning Multiverse
Samuel J. Bell, Onno Kampman, Jesse Dodge et al.
Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings
Dongxu Zhang, Michael Boratko, Cameron Musco et al.
Model Preserving Compression for Neural Networks
Jerry Chee, Megan Flynn (née Renz), Anil Damle et al.
Models Out of Line: A Fourier Lens on Distribution Shift Robustness
Sara Fridovich-Keil, Brian Bartoldson, James Diffenderfer et al.
Model Zoos: A Dataset of Diverse Populations of Neural Network Models
Konstantin Schürholt, Diyar Taskiran, Boris Knyazev et al.
Moderate-fitting as a Natural Backdoor Defender for Pre-trained Language Models
Biru Zhu, Yujia Qin, Ganqu Cui et al.