"gradient descent optimization" Papers

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Variational Inference with Mixtures of Isotropic Gaussians

Marguerite Petit-Talamon, Marc Lambert, Anna Korba

NeurIPS 2025posterarXiv:2506.13613

Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data

Xuran Meng, Difan Zou, Yuan Cao

ICML 2024poster

How Graph Neural Networks Learn: Lessons from Training Dynamics

Chenxiao Yang, Qitian Wu, David Wipf et al.

ICML 2024poster

Improving Sharpness-Aware Minimization by Lookahead

Runsheng Yu, Youzhi Zhang, James Kwok

ICML 2024poster

LoRA Training in the NTK Regime has No Spurious Local Minima

Uijeong Jang, Jason Lee, Ernest Ryu

ICML 2024poster

Offline and Online Optical Flow Enhancement for Deep Video Compression

Chuanbo Tang, Xihua Sheng, Zhuoyuan Li et al.

AAAI 2024paperarXiv:2307.05092

QLABGrad: A Hyperparameter-Free and Convergence-Guaranteed Scheme for Deep Learning

Fang-Xiang Wu, Minghan Fu

AAAI 2024paperarXiv:2302.00252

Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians

Tom Huix, Anna Korba, Alain Oliviero Durmus et al.

ICML 2024poster