9 papers
Non-Stationary Bandit Convex Optimization: An Optimal Algorithm with Two-Point Feedback
Chang He, Bo Jiang, Shuzhong Zhang
This paper studies bandit convex optimization in non-stationary environments with two-point feedback, using dynamic regret as the performance measure. We propose an algorithm based…
On the Nature of Regularity Assumptions in Bilevel Optimization with Constrained Lower-level Problem
Xiaotian Jiang, Chang He, Mingyi Hong +1
In this paper, we study the regularity assumptions commonly adopted in bilevel optimization with constrained lower-level problems, including the linear independence constraint qual…
Adaptive Single-Loop Methods for Stochastic Minimax Optimization on Riemannian Manifolds
Hongye Wang, Chang He, Bo Jiang
Stochastic minimax optimization on Riemannian manifolds has recently attracted significant attention due to its broad range of applications, such as robust training of neural netwo…
Beyond Nonconvexity: A Universal Trust-Region Method with New Analyses
Yuntian Jiang, Chang He, Chuwen Zhang +3
The trust-region (TR) method is renowned historically for its robustness in nonconvex problems and extraordinary numerical performance, but the study of its performance in convex o…
On Approximation Algorithms for Commutative Quaternion Polynomial Optimization
Chang He, Bo Jiang, Hongye Wang +1
Quaternion optimization has attracted significant interest due to its broad applications, including color face recognition, video compression, and signal processing. Despite the gr…
History-Aware Adaptive High-Order Tensor Regularization
Chang He, Bo Jiang, Yuntian Jiang +2
In this paper, we develop a new adaptive regularization method for minimizing a composite function, which is the sum of a th-order () Lipschitz continuous function and…