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Home/Authors/Meng Wang

Meng Wang

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

ML×2AI×2Crypto×1

Frequent co-authors

Yunwen Lei2×
Zimeng Wang2×
Xiaoming Yuan2×
Yue Ma1×
Majid Garoosi1×
Wenting Fan1×

Research Timeline

2026
Stochastic Gradient Descent with Momentum is Algorithmically Stable

This paper provides a comprehensive generalization analysis of Stochastic Gradient Descent with Momentum (SGDM) by establishing tight, on-average model stability bounds that show SGDM can generalize well to unseen data.

Learning Theory of the SVRG: Generalization and Convergence Analysis

This paper provides the first non-vacuous generalization analysis for the Stochastic Variance Reduced Gradient (SVRG) method by establishing sharp, data-dependent algorithmic stability bounds, thereby clarifying the link between optimization and generalization.

PyFEX: Uncovering Evasive Python-based Threats via Resilient and Exhaustive Path Exploration

PyFEX introduces a resilient forced-execution engine to exhaustively analyze Python code, successfully detecting previously unknown malicious packages and binaries in the Python ecosystem.

Highlighted terms show continued research focus across papers

Papers

cs.CRRecentJun 1, 2026

PyFEX: Uncovering Evasive Python-based Threats via Resilient and Exhaustive Path Exploration

Meng Wang, Yue Ma, Majid Garoosi, Wenting Fan +3 more

PyFEX introduces a resilient forced-execution engine to exhaustively analyze Python code, successfully detecting previously unknown malicious packages and binaries in the Python ecosystem.

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cs.LGcs.AIRecentMay 27, 2026

Stochastic Gradient Descent with Momentum is Algorithmically Stable

Yunwen Lei, Zimeng Wang, Xiaoming Yuan

This paper provides a comprehensive generalization analysis of Stochastic Gradient Descent with Momentum (SGDM) by establishing tight, on-average model stability bounds that show SGDM can generalize w…

View →
cs.LGcs.AIRecentMay 27, 2026

Learning Theory of the SVRG: Generalization and Convergence Analysis

Yunwen Lei, Zimeng Wang, Xiaoming Yuan

This paper provides the first non-vacuous generalization analysis for the Stochastic Variance Reduced Gradient (SVRG) method by establishing sharp, data-dependent algorithmic stability bounds, thereby…

View →