research
∙
07/31/2023
Discovering Adaptable Symbolic Algorithms from Scratch
Autonomous robots deployed in the real world will need control policies ...
share
research
∙
02/13/2023
Symbolic Discovery of Optimization Algorithms
We present a method to formulate algorithm discovery as program search, ...
research
∙
02/10/2023
Unified Functional Hashing in Automatic Machine Learning
The field of Automatic Machine Learning (AutoML) has recently attained i...
research
∙
02/03/2023
PyGlove: Efficiently Exchanging ML Ideas as Code
The increasing complexity and scale of machine learning (ML) has led to ...
research
∙
04/08/2022
Multi-objective evolution for Generalizable Policy Gradient Algorithms
Performance, generalizability, and stability are three Reinforcement Lea...
research
∙
01/21/2021
PyGlove: Symbolic Programming for Automated Machine Learning
Neural networks are sensitive to hyper-parameter and architecture choice...
research
∙
01/08/2021
Evolving Reinforcement Learning Algorithms
We propose a method for meta-learning reinforcement learning algorithms ...
research
∙
03/06/2020
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Machine learning research has advanced in multiple aspects, including mo...
research
∙
02/25/2019
NAS-Bench-101: Towards Reproducible Neural Architecture Search
Recent advances in neural architecture search (NAS) demand tremendous co...
research
∙
02/05/2018
Regularized Evolution for Image Classifier Architecture Search
The effort devoted to hand-crafting image classifiers has motivated the ...
research
∙
03/03/2017
Large-Scale Evolution of Image Classifiers
Neural networks have proven effective at solving difficult problems but ...
research
∙
02/02/2017
YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video
We introduce a new large-scale data set of video URLs with densely-sampl...
research
∙
12/22/2014