2025 Poster "stochastic gradient descent" Papers
17 papers found
Controlling the Flow: Stability and Convergence for Stochastic Gradient Descent with Decaying Regularization
Sebastian Kassing, Simon Weissmann, Leif Döring
NEURIPS 2025posterarXiv:2505.11434
1
citations
Convergence of Clipped SGD on Convex $(L_0,L_1)$-Smooth Functions
Ofir Gaash, Kfir Y. Levy, Yair Carmon
NEURIPS 2025posterarXiv:2502.16492
4
citations
Descent with Misaligned Gradients and Applications to Hidden Convexity
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar et al.
ICLR 2025poster
Emergence and scaling laws in SGD learning of shallow neural networks
Yunwei Ren, Eshaan Nichani, Denny Wu et al.
NEURIPS 2025posterarXiv:2504.19983
13
citations
Gaussian Approximation and Concentration of Constant Learning-Rate Stochastic Gradient Descent
Ziyang Wei, Jiaqi Li, Zhipeng Lou et al.
NEURIPS 2025poster
Gradient correlation is a key ingredient to accelerate SGD with momentum
Julien Hermant, Marien Renaud, Jean-François Aujol et al.
ICLR 2025posterarXiv:2410.07870
2
citations
Leveraging Flatness to Improve Information-Theoretic Generalization Bounds for SGD
Ze Peng, Jian Zhang, Yisen Wang et al.
ICLR 2025posterarXiv:2601.01465
Neural Thermodynamics: Entropic Forces in Deep and Universal Representation Learning
Liu Ziyin, Yizhou Xu, Isaac Chuang
NEURIPS 2025posterarXiv:2505.12387
4
citations
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation
Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus et al.
ICLR 2025posterarXiv:2410.05106
4
citations
Online robust locally differentially private learning for nonparametric regression
Chenfei Gu, Qiangqiang Zhang, Ting Li et al.
NEURIPS 2025poster
Online Statistical Inference in Decision Making with Matrix Context
Qiyu Han, Will Wei Sun, Yichen Zhang
NEURIPS 2025posterarXiv:2212.11385
2
citations
On the Convergence of Stochastic Smoothed Multi-Level Compositional Gradient Descent Ascent
Xinwen Zhang, Hongchang Gao
NEURIPS 2025poster
Optimal Rates in Continual Linear Regression via Increasing Regularization
Ran Levinstein, Amit Attia, Matan Schliserman et al.
NEURIPS 2025posterarXiv:2506.06501
2
citations
Revisiting Large-Scale Non-convex Distributionally Robust Optimization
Qi Zhang, Yi Zhou, Simon Khan et al.
ICLR 2025poster
1
citations
Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations
Shaocong Ma, Heng Huang
ICLR 2025posterarXiv:2510.19975
12
citations
Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation
Chenyu Zhang, Xu Chen, Xuan Di
ICLR 2025posterarXiv:2408.08192
7
citations
Understanding the Generalization of Stochastic Gradient Adam in Learning Neural Networks
Xuan Tang, Han Zhang, Yuan Cao et al.
NEURIPS 2025posterarXiv:2510.11354