Papers
Margin-based sampling in high dimensions: When being active is less efficient than staying passive
Alexandru Tifrea, Jacob Clarysse, Fanny Yang
Markovian Gaussian Process Variational Autoencoders
Harrison Zhu, Carles Balsells-Rodas, Yingzhen Li
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference
Insung Kong, Dongyoon Yang, Jongjin Lee et al.
Masked Trajectory Models for Prediction, Representation, and Control
Philipp Wu, Arjun Majumdar, Kevin Stone et al.
Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning
Zhongzhi Yu, Yang Zhang, Kaizhi Qian et al.
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen et al.
Matrix Estimation for Individual Fairness
Cindy Zhang, Sarah Huiyi Cen, Devavrat Shah
Maximal Initial Learning Rates in Deep ReLU Networks
Gaurav Iyer, Boris Hanin, David Rolnick
Maximum Optimality Margin: A Unified Approach for Contextual Linear Programming and Inverse Linear Programming
Chunlin Sun, Shang Liu, Xiaocheng Li
Measuring the Impact of Programming Language Distribution
Gabriel Orlanski, Kefan Xiao, Xavier Garcia et al.
Mechanistic Mode Connectivity
Ekdeep Singh Lubana, Eric J Bigelow, Robert P. Dick et al.
Memory-Based Dual Gaussian Processes for Sequential Learning
Paul Edmund Chang, Prakhar Verma, S. T. John et al.
Memory-Based Meta-Learning on Non-Stationary Distributions
Tim Genewein, Gregoire Deletang, Anian Ruoss et al.
Men Also Do Laundry: Multi-Attribute Bias Amplification
Dora Zhao, Jerone Andrews, Alice Xiang
MetaDiffuser: Diffusion Model as Conditional Planner for Offline Meta-RL
Fei Ni, Jianye Hao, Yao Mu et al.
Metagenomic Binning using Connectivity-constrained Variational Autoencoders
Andre Lamurias, Alessandro Tibo, Katja Hose et al.
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks
Shibo Li, Michael Penwarden, Yiming Xu et al.
Meta-learning Parameterized Skills
Haotian Fu, Shangqun Yu, Saket Tiwari et al.
Meta-Learning the Inductive Bias of Simple Neural Circuits
Will Dorrell, Maria Yuffa, Peter E. Latham
MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks
Wenfang Sun, Yingjun Du, Xiantong Zhen et al.
Meta Optimal Transport
Brandon Amos, Giulia Luise, Samuel Cohen et al.
Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optimization
Jiwoo Son, Minsu Kim, Hyeonah Kim et al.
MetricGAN-OKD: Multi-Metric Optimization of MetricGAN via Online Knowledge Distillation for Speech Enhancement
Wooseok Shin, Byung Hoon Lee, Jin Sob Kim et al.
MEWL: Few-shot multimodal word learning with referential uncertainty
Guangyuan Jiang, Manjie Xu, Shiji Xin et al.
MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods
Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman et al.