Papers
Mimetic Initialization of Self-Attention Layers
Asher Trockman, J Zico Kolter
Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints
Alexandra Anna Lassota, Alexander Lindermayr, Nicole Megow et al.
Minimax estimation of discontinuous optimal transport maps: The semi-discrete case
Aram-Alexandre Pooladian, Vincent Divol, Jonathan Niles-Weed
Minimizing Trajectory Curvature of ODE-based Generative Models
Sangyun Lee, Beomsu Kim, Jong Chul Ye
Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation
Li’Ang Li, Yifei Duan, Guanghua Ji et al.
Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes
Marin Ballu, Quentin Berthet
Mitigating Memorization of Noisy Labels by Clipping the Model Prediction
Hongxin Wei, Huiping Zhuang, Renchunzi Xie et al.
Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling
Arka Daw, Jie Bu, Sifan Wang et al.
Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning
Yu Yang, Besmira Nushi, Hamid Palangi et al.
MixFlows: principled variational inference via mixed flows
Zuheng Xu, Naitong Chen, Trevor Campbell
Mixing Predictions for Online Metric Algorithms
Antonios Antoniadis, Christian Coester, Marek Elias et al.
Mixture Proportion Estimation Beyond Irreducibility
Yilun Zhu, Aaron Fjeldsted, Darren Holland et al.
Moccasin: Efficient Tensor Rematerialization for Neural Networks
Burak Bartan, Haoming Li, Harris Teague et al.
Modality-Agnostic Variational Compression of Implicit Neural Representations
Jonathan Richard Schwarz, Jihoon Tack, Yee Whye Teh et al.
Model-agnostic Measure of Generalization Difficulty
Akhilan Boopathy, Kevin Liu, Jaedong Hwang et al.
Model-Aware Contrastive Learning: Towards Escaping the Dilemmas
Zizheng Huang, Haoxing Chen, Ziqi Wen et al.
Model-based Offline Reinforcement Learning with Count-based Conservatism
Byeongchan Kim, Min-Hwan Oh
Model-based Reinforcement Learning with Scalable Composite Policy Gradient Estimators
Paavo Parmas, Takuma Seno, Yuma Aoki
Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning
Yihao Sun, Jiaji Zhang, Chengxing Jia et al.
ModelDiff: A Framework for Comparing Learning Algorithms
Harshay Shah, Sung Min Park, Andrew Ilyas et al.
Model-Free Robust Average-Reward Reinforcement Learning
Yue Wang, Alvaro Velasquez, George K. Atia et al.
Modeling Dynamic Environments with Scene Graph Memory
Andrey Kurenkov, Michael Lingelbach, Tanmay Agarwal et al.
Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion
Marin Biloš, Kashif Rasul, Anderson Schneider et al.
MODeL: Memory Optimizations for Deep Learning
Benoit Steiner, Mostafa Elhoushi, Jacob Kahn et al.
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization
Alexandre Rame, Kartik Ahuja, Jianyu Zhang et al.