5 citations · 8 across the 17 of their papers we have counts for
8 papers · 1 filter
Optimization under Persistent State-Dependent Bias: Gradient-based Method and Complexity Analysis
Zhaoxian Wu, Quan Xiao, Tayfun Gokmen +1
This paper studies the convergence of stochastic gradient descent (SGD) when the implemented updates are subject to a persistent and state-dependent bias, in which the desired upda…
Efficient Penalty-Based Bilevel Methods: Improved Analysis, Novel Updates, and Flatness Condition
Liuyuan Jiang, Quan Xiao, Lisha Chen +1
Penalty-based methods have become popular for solving bilevel optimization (BLO) problems, thanks to their effective first-order nature. However, they often require inner-loop iter…
Beyond Value Functions: Single-Loop Bilevel Optimization under Flatness Conditions
Liuyuan Jiang, Quan Xiao, Lisha Chen +1
Bilevel optimization, a hierarchical optimization paradigm, has gained significant attention in a wide range of practical applications, notably in the fine-tuning of generative mod…
Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance
Lisha Chen, Quan Xiao, Ellen Hidemi Fukuda +3
Multi-objective learning under user-specified preference is common in real-world problems such as multi-lingual speech recognition under fairness. In this work, we frame such a pro…
Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
Quan Xiao, Tianyi Chen
Bilevel optimization has witnessed a resurgence of interest, driven by its critical role in trustworthy and efficient AI applications. While many recent works have established conv…
A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints
Liuyuan Jiang, Quan Xiao, Victor M. Tenorio +3
Interest in bilevel optimization has grown in recent years, partially due to its applications to tackle challenging machine-learning problems. Several exciting recent works have be…
A Bilevel Optimization Method for Inverse Mean-Field Games
Jiajia Yu, Quan Xiao, Tianyi Chen +1
In this paper, we introduce a bilevel optimization framework for addressing inverse mean-field games, alongside an exploration of numerical methods tailored for this bilevel proble…
A Generalized Alternating Method for Bilevel Learning under the Polyak-Łojasiewicz Condition
Quan Xiao, Songtao Lu, Tianyi Chen
Bilevel optimization has recently regained interest owing to its applications in emerging machine learning fields such as hyperparameter optimization, meta-learning, and reinforcem…