Efficient Quality-Diversity Optimization through Diverse Quality Species

1 code implementation • 14 Apr 2023 • Ryan Wickman, Bibek Poudel, Michael Villarreal, Xiaofei Zhang, Weizi Li

This can be rectified by Quality-Diversity (QD) algorithms, where a population of high-quality and diverse solutions to a problem is preferred.

AutoJoin: Efficient Adversarial Training for Robust Maneuvering via Denoising Autoencoder and Joint Learning

no code implementations • 22 May 2022 • Michael Villarreal, Bibek Poudel, Ryan Wickman, Yu Shen, Weizi Li

As a result of increasingly adopted machine learning algorithms and ubiquitous sensors, many 'perception-to-control' systems are developed and deployed.

Denoising

A Generic Graph Sparsification Framework using Deep Reinforcement Learning

1 code implementation • 2 Dec 2021 • Ryan Wickman, Xiaofei Zhang, Weizi Li

The interconnectedness and interdependence of modern graphs are growing ever more complex, causing enormous resources for processing, storage, communication, and decision-making of these graphs.

Decision Making reinforcement-learning +1

LRN: Limitless Routing Networks for Effective Multi-task Learning

no code implementations • 29 Sep 2021 • Ryan Wickman, Xiaofei Zhang, Weizi Li

Multi-task learning (MTL) is a field involved with learning multiple tasks simultaneously typically through using shared model parameters.

Multi-Task Learning