Poster "optimizer design" Papers

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Adam Reduces a Unique Form of Sharpness: Theoretical Insights Near the Minimizer Manifold

Xinghan Li, Haodong Wen, Kaifeng Lyu

NEURIPS 2025arXiv:2511.02773

Gradient Multi-Normalization for Efficient LLM Training

Meyer Scetbon, Chao Ma, Wenbo Gong et al.

LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization

Jui-Nan Yen, Si Si, Zhao Meng et al.

ICLR 2025arXiv:2410.20625

On the Performance Analysis of Momentum Method: A Frequency Domain Perspective

Xianliang Li, Jun Luo, Zhiwei Zheng et al.

ICLR 2025arXiv:2411.19671

The AdEMAMix Optimizer: Better, Faster, Older

Matteo Pagliardini, Pierre Ablin, David Grangier

ICLR 2025arXiv:2409.03137

Scaling Exponents Across Parameterizations and Optimizers

Katie Everett, Lechao Xiao, Mitchell Wortsman et al.

ICML 2024arXiv:2407.05872

Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise

Kwangjun Ahn, Zhiyu Zhang, Yunbum Kook et al.

ICML 2024arXiv:2402.01567