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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...
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05/30/2023
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning
Federated bilevel optimization (FBO) has shown great potential recently ...
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05/28/2023
Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms
Multi-objective optimization (MOO) has become an influential framework i...
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02/10/2023
Achieving Linear Speedup in Non-IID Federated Bilevel Learning
Federated bilevel optimization has received increasing attention in vari...
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02/09/2023
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation
Federated bilevel optimization has attracted increasing attention due to...
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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...
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05/27/2022
Will Bilevel Optimizers Benefit from Loops
Bilevel optimization has arisen as a powerful tool for solving a variety...
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03/31/2022
Data Sampling Affects the Complexity of Online SGD over Dependent Data
Conventional machine learning applications typically assume that data sa...
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03/01/2022
A Constrained Optimization Approach to Bilevel Optimization with Multiple Inner Minima
Bilevel optimization has found extensive applications in modern machine ...
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02/08/2022
Efficiently Escaping Saddle Points in Bilevel Optimization
Bilevel optimization is one of the fundamental problems in machine learn...
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10/13/2021
ES-Based Jacobian Enables Faster Bilevel Optimization
Bilevel optimization (BO) has arisen as a powerful tool for solving many...
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07/31/2021
Bilevel Optimization for Machine Learning: Algorithm Design and Convergence Analysis
Bilevel optimization has become a powerful framework in various machine ...
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06/08/2021
Provably Faster Algorithms for Bilevel Optimization
Bilevel optimization has been widely applied in many important machine l...
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02/07/2021
Lower Bounds and Accelerated Algorithms for Bilevel Optimization
Bilevel optimization has recently attracted growing interests due to its...
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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...
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10/14/2020
Boosting One-Point Derivative-Free Online Optimization via Residual Feedback
Zeroth-order optimization (ZO) typically relies on two-point feedback to...
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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 ...
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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...
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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...
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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...
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02/17/2020
Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack
The multi-armed bandit formalism has been extensively studied under vari...
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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...
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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...
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02/07/2019
Momentum Schemes with Stochastic Variance Reduction for Nonconvex Composite Optimization
Two new stochastic variance-reduced algorithms named SARAH and SPIDER ha...
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11/02/2018
Minimax Estimation of Neural Net Distance
An important class of distance metrics proposed for training generative ...
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10/25/2018
SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization
There has been extensive research on developing stochastic variance redu...
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06/12/2018
Convergence of SGD in Learning ReLU Models with Separable Data
We consider the binary classification problem in which the objective fun...
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02/16/2018
Learning Latent Features with Pairwise Penalties in Matrix Completion
Low-rank matrix completion (MC) has achieved great success in many real-...
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01/08/2018
Asymptotic Miss Ratio of LRU Caching with Consistent Hashing
To efficiently scale data caching infrastructure to support emerging big...
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08/04/2017
