16 citations · 31 across the 7 of their papers we have counts for
10 papers · 1 filter
Data Sampling Affects the Complexity of Online SGD over Dependent Data
Shaocong Ma, Ziyi Chen, Yi Zhou +2
Conventional machine learning applications typically assume that data samples are independently and identically distributed (i.i.d.). However, practical scenarios often involve a d…
Bilevel Optimization for Machine Learning: Algorithm Design and Convergence Analysis
Kaiyi Ji
Bilevel optimization has become a powerful framework in various machine learning applications including meta-learning, hyperparameter optimization, and network architecture search.…
Bilevel Optimization: Convergence Analysis and Enhanced Design
Kaiyi Ji, Junjie Yang, Yingbin Liang
Bilevel optimization has arisen as a powerful tool for many machine learning problems such as meta-learning, hyperparameter optimization, and reinforcement learning. In this paper,…
Boosting One-Point Derivative-Free Online Optimization via Residual Feedback
Yan Zhang, Yi Zhou, Kaiyi Ji +1
Zeroth-order optimization (ZO) typically relies on two-point feedback to estimate the unknown gradient of the objective function. Nevertheless, two-point feedback can not be used f…
Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters
Kaiyi Ji, Jason D. Lee, Yingbin Liang +1
Although model-agnostic meta-learning (MAML) is a very successful algorithm in meta-learning practice, it can have high computational cost because it updates all model parameters o…
Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack
Ziwei Guan, Kaiyi Ji, Donald J Bucci +4
The multi-armed bandit formalism has been extensively studied under various attack models, in which an adversary can modify the reward revealed to the player. Previous studies focu…