research
∙
09/07/2023
Large Language Models as Optimizers
Optimization is ubiquitous. While derivative-based algorithms have been ...
share
research
∙
04/15/2022
Resource-Constrained Neural Architecture Search on Tabular Datasets
The best neural architecture for a given machine learning problem depend...
research
∙
06/17/2021
How Low Can We Go: Trading Memory for Error in Low-Precision Training
Low-precision arithmetic trains deep learning models using less energy, ...
research
∙
01/01/2021
TenIPS: Inverse Propensity Sampling for Tensor Completion
Tensors are widely used to represent multiway arrays of data. The recove...
research
∙
12/07/2020
Low-Rank Tensor Recovery with Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization
The nuclear norm and Schatten-p quasi-norm of a matrix are popular rank ...
research
∙
06/07/2020
Efficient AutoML Pipeline Search with Matrix and Tensor Factorization
Data scientists seeking a good supervised learning model on a new datase...
research
∙
05/04/2020
Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering
Low dimensional nonlinear structure abounds in datasets across computer ...
research
∙
08/09/2018