Papers
Transformative or Conservative? Conservation laws for ResNets and Transformers
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity
Arto Maranjyan, Alexander Tyurin, Peter Richtárik
ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
Arto Maranjyan, El Mehdi Saad, Peter Richtárik et al.
Principled Algorithms for Optimizing Generalized Metrics in Binary Classification
Anqi Mao, Mehryar Mohri, Yutao Zhong
Mastering Multiple-Expert Routing: Realizable H-Consistency and Strong Guarantees for Learning to Defer
Anqi Mao, Mehryar Mohri, Yutao Zhong
Hypo3D: Exploring Hypothetical Reasoning in 3D
Ye Mao, Weixun Luo, Junpeng Jing et al.
CTBench: A Library and Benchmark for Certified Training
Yuhao Mao, Stefan Balauca, Martin Vechev
Efficient Diffusion Models for Symmetric Manifolds
Oren Mangoubi, Neil He, Nisheeth K. Vishnoi
Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up
Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut et al.
Learning Latent Graph Structures and their Uncertainty
Alessandro Manenti, Daniele Zambon, Cesare Alippi
Potemkin Understanding in Large Language Models
Marina Mancoridis, Bec Weeks, Keyon Vafa et al.
Emergence in non-neural models: grokking modular arithmetic via average gradient outer product
Neil Rohit Mallinar, Daniel Beaglehole, Libin Zhu et al.
Reasoning Limitations of Multimodal Large Language Models. A case study of Bongard Problems
Mikołaj Małkiński, Szymon Pawlonka, Jacek Mańdziuk
Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments
Mikel Malagón, Josu Ceberio, Jose A. Lozano
Hypothesis Testing for Generalized Thurstone Models
Anuran Makur, Japneet Singh
Residual Matrix Transformers: Scaling the Size of the Residual Stream
Brian Mak, Jeffrey Flanigan
Regret-Free Reinforcement Learning for Temporal Logic Specifications
R Majumdar, Mahmoud Salamati, Sadegh Soudjani
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi Gnvv et al.
SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding
Peihua Mai, Youlong Ding, Ziyan Lyu et al.
Auditing f-differential privacy in one run
Saeed Mahloujifar, Luca Melis, Kamalika Chaudhuri
Sable: a Performant, Efficient and Scalable Sequence Model for MARL
Omayma Mahjoub, Sasha Abramowitz, Ruan John De Kock et al.
Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation
Sadegh Mahdavi, Muchen Li, Kaiwen Liu et al.
Compositional Risk Minimization
Divyat Mahajan, Mohammad Pezeshki, Charles Arnal et al.
DataDecide: How to Predict Best Pretraining Data with Small Experiments
Ian Magnusson, Nguyen Tai, Ben Bogin et al.
Learning to Stop: Deep Learning for Mean Field Optimal Stopping
Lorenzo Magnino, Yuchen Zhu, Mathieu Lauriere