Search Results for author: Yue-Jiao Gong

Found 10 papers, 5 papers with code

RLEMMO: Evolutionary Multimodal Optimization Assisted By Deep Reinforcement Learning

no code implementations12 Apr 2024 Hongqiao Lian, Zeyuan Ma, Hongshu Guo, Ting Huang, Yue-Jiao Gong

In this paper, we propose RLEMMO, a Meta-Black-Box Optimization framework, which maintains a population of solutions and incorporates a reinforcement learning agent for flexibly adjusting individual-level searching strategies to match the up-to-date optimization status, hence boosting the search performance on MMOP.

Diversity reinforcement-learning

Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learning

no code implementations12 Apr 2024 Zeyuan Ma, Jiacheng Chen, Hongshu Guo, Yining Ma, Yue-Jiao Gong

Evolutionary computation (EC) algorithms, renowned as powerful black-box optimizers, leverage a group of individuals to cooperatively search for the optimum.

LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation

no code implementations2 Mar 2024 Zeyuan Ma, Hongshu Guo, Jiacheng Chen, Guojun Peng, Zhiguang Cao, Yining Ma, Yue-Jiao Gong

Recent research explores optimization using large language models (LLMs) by either iteratively seeking next-step solutions from LLMs or directly prompting LLMs for an optimizer.

Code Generation Contrastive Learning

Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning

1 code implementation4 Feb 2024 Jiacheng Chen, Zeyuan Ma, Hongshu Guo, Yining Ma, Jie Zhang, Yue-Jiao Gong

Recent Meta-learning for Black-Box Optimization (MetaBBO) methods harness neural networks to meta-learn configurations of traditional black-box optimizers.

Meta-Learning Zero-shot Generalization

MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning

1 code implementation NeurIPS 2023 Zeyuan Ma, Hongshu Guo, Jiacheng Chen, Zhenrui Li, Guojun Peng, Yue-Jiao Gong, Yining Ma, Zhiguang Cao

To fill this gap, we introduce MetaBox, the first benchmark platform expressly tailored for developing and evaluating MetaBBO-RL methods.

Benchmarking

Multi-task Learning for Sparse Traffic Forecasting

2 code implementations18 Nov 2022 Jiezhang Li, Junjun Li, Yue-Jiao Gong

For this reason, we propose a multi-task learning network that can simultaneously predict the congestion classes and the speed of each road segment.

Graph Neural Network Multi-Task Learning +1

Real-Time Traffic Signal Control for Modern Roundabouts by Using Particle Swarm Optimization-Based Fuzzy Controller

no code implementations4 Aug 2014 Yue-Jiao Gong, Jun Zhang

This mechanism helps to instantly respond to the current traffic condition of the roundabout so as to improve real-timeness.

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