b'Kaiyi Ji'

research

∙ 08/07/2023

Non-Convex Bilevel Optimization with Time-Varying Objective Functions

Bilevel optimization has become a powerful tool in a wide variety of mac...

0 Sen Lin, et al. ∙

research

∙ 05/30/2023

SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning

Federated bilevel optimization (FBO) has shown great potential recently ...

0 Yifan Yang, et al. ∙

research

∙ 05/28/2023

Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms

Multi-objective optimization (MOO) has become an influential framework i...

0 Peiyao Xiao, et al. ∙

research

∙ 02/10/2023

Achieving Linear Speedup in Non-IID Federated Bilevel Learning

Federated bilevel optimization has received increasing attention in vari...

0 Minhui Huang, et al. ∙

research

∙ 02/09/2023

Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation

Federated bilevel optimization has attracted increasing attention due to...

0 Peiyao Xiao, et al. ∙

research

∙ 01/04/2023

Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach

Fair resource allocation is one of the most important topics in communic...

0 Kaiyi Ji, et al. ∙

research

∙ 05/27/2022

Will Bilevel Optimizers Benefit from Loops

Bilevel optimization has arisen as a powerful tool for solving a variety...

7 Kaiyi Ji, et al. ∙

research

∙ 03/31/2022

Data Sampling Affects the Complexity of Online SGD over Dependent Data

Conventional machine learning applications typically assume that data sa...

0 Shaocong Ma, et al. ∙

research

∙ 03/01/2022

A Constrained Optimization Approach to Bilevel Optimization with Multiple Inner Minima

Bilevel optimization has found extensive applications in modern machine ...

0 Daouda Sow, et al. ∙

research

∙ 02/08/2022

Efficiently Escaping Saddle Points in Bilevel Optimization

Bilevel optimization is one of the fundamental problems in machine learn...

0 Minhui Huang, et al. ∙

research

∙ 10/13/2021

ES-Based Jacobian Enables Faster Bilevel Optimization

Bilevel optimization (BO) has arisen as a powerful tool for solving many...

0 Daouda Sow, et al. ∙

research

∙ 07/31/2021

Bilevel Optimization for Machine Learning: Algorithm Design and Convergence Analysis

Bilevel optimization has become a powerful framework in various machine ...

0 Kaiyi Ji, et al. ∙

research

∙ 06/08/2021

Provably Faster Algorithms for Bilevel Optimization

Bilevel optimization has been widely applied in many important machine l...

0 Junjie Yang, et al. ∙

research

∙ 02/07/2021

Lower Bounds and Accelerated Algorithms for Bilevel Optimization

Bilevel optimization has recently attracted growing interests due to its...

0 Kaiyi Ji, et al. ∙

research

∙ 10/15/2020

Provably Faster Algorithms for Bilevel Optimization and Applications to Meta-Learning

Bilevel optimization has arisen as a powerful tool for many machine lear...

0 Kaiyi Ji, et al. ∙

research

∙ 10/14/2020

Boosting One-Point Derivative-Free Online Optimization via Residual Feedback

Zeroth-order optimization (ZO) typically relies on two-point feedback to...

10 Yan Zhang, et al. ∙

research

∙ 06/18/2020

Improving the Convergence Rate of One-Point Zeroth-Order Optimization using Residual Feedback

Many existing zeroth-order optimization (ZO) algorithms adopt two-point ...

0 Yan Zhang, et al. ∙

research

∙ 06/16/2020

Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters

Although model-agnostic meta-learning (MAML) is a very successful algori...

0 Kaiyi Ji, et al. ∙

research

∙ 02/26/2020

Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization

Various types of parameter restart schemes have been proposed for accele...

0 Yi Zhou, et al. ∙

research

∙ 02/18/2020

Multi-Step Model-Agnostic Meta-Learning: Convergence and Improved Algorithms

As a popular meta-learning approach, the model-agnostic meta-learning (M...

7 Kaiyi Ji, et al. ∙

research

∙ 02/17/2020

Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack

The multi-armed bandit formalism has been extensively studied under vari...

14 Ziwei Guan, et al. ∙

research

∙ 10/27/2019

Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization

Two types of zeroth-order stochastic algorithms have recently been desig...

36 Kaiyi Ji, et al. ∙

research

∙ 10/21/2019

Faster Stochastic Algorithms via History-Gradient Aided Batch Size Adaptation

Various schemes for adapting batch size have been recently proposed to a...

22 Kaiyi Ji, et al. ∙

research

∙ 02/07/2019

Momentum Schemes with Stochastic Variance Reduction for Nonconvex Composite Optimization

Two new stochastic variance-reduced algorithms named SARAH and SPIDER ha...

0 Yi Zhou, et al. ∙

research

∙ 11/02/2018

Minimax Estimation of Neural Net Distance

An important class of distance metrics proposed for training generative ...

0 Kaiyi Ji, et al. ∙

research

∙ 10/25/2018

SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization

There has been extensive research on developing stochastic variance redu...

9 Zhe Wang, et al. ∙

research

∙ 06/12/2018

Convergence of SGD in Learning ReLU Models with Separable Data

We consider the binary classification problem in which the objective fun...

0 Tengyu Xu, et al. ∙

research

∙ 02/16/2018

Learning Latent Features with Pairwise Penalties in Matrix Completion

Low-rank matrix completion (MC) has achieved great success in many real-...

0 Kaiyi Ji, et al. ∙

research

∙ 01/08/2018

Asymptotic Miss Ratio of LRU Caching with Consistent Hashing

To efficiently scale data caching infrastructure to support emerging big...

0 Kaiyi Ji, et al. ∙

research

∙ 08/04/2017

On Resource Pooling and Separation for LRU Caching

Caching systems using the Least Recently Used (LRU) principle have now b...

0 Jian Tan, et al. ∙

Kaiyi Ji

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