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cs.LG2026
Distribution-Aware Robust Bilevel Optimization: Quantile-Guided Huber Updates in Two-Timescale Stochastic Approximation
Zhiyu Li, Xi Xuan, Davide Carbone
Bilevel optimization (BLO) is fundamental to hierarchical decision-making but suffers from critical instability under heavy-tailed stochastic noise. Existing variance-reduction tec…
cs.LG2026
Escaping the Variance Trap: Jacobian-Free Dynamics for Root-Finding Bilevel Optimization
Zhiyu Li, Xi Xuan, Davide Carbone
Many central machine learning tasks, from entropy tuning in reinforcement learning to equilibrating generative adversarial networks, are fundamentally stochastic root-finding probl…
cs.LG2025
Wavelet Scattering Transform and Fourier Representation for Offline Detection of Malicious Clients in Federated Learning
Alessandro Licciardi, Davide Leo, Davide Carbone
Federated Learning (FL) enables the training of machine learning models across decentralized clients while preserving data privacy. However, the presence of anomalous or corrupted…