Seven papers accepted to ICML 2026
Seven papers from the group were accepted to ICML 2026, spanning efficient LLM training and inference, AI for Math, and optimization theory.
Updates, papers, awards, talks, and announcements from the MELON Research Group.
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Seven papers from the group were accepted to ICML 2026, spanning efficient LLM training and inference, AI for Math, and optimization theory.
Two papers were accepted: one to IEEE TPAMI on communication-efficient distributed learning under data heterogeneity, and one to TMLR on domain weight randomization for LLM pre-training.
Kun Yuan will serve as an Associate Editor for IEEE Transactions on Signal Processing.
We are hiring postdocs and undergraduate research interns. If you are interested in machine learning, optimization, and AI systems, please get in touch.
Gave a one-hour invited talk on Memory-Efficient LLM Training via Implicit Structures at the Microsoft Research Asia ACE Talk.
Three papers were accepted to the Journal of Machine Learning Research, on decentralized bilevel optimization, gradient normalization under heavy-tailed noise, and Byzantine-robust distributed optimization.
Three papers were accepted to NeurIPS 2025 on fault-tolerant and memory-efficient LLM optimization and efficient model representation.
Five papers were accepted to ICML 2025, including two Spotlights, covering multi-objective learning, decentralized optimization over row-stochastic networks, and subspace optimization for LLMs.