Chengrun Yang | DeepAI

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∙ 09/07/2023

Large Language Models as Optimizers

Optimization is ubiquitous. While derivative-based algorithms have been ...

0 Chengrun Yang, et al. ∙

∙ 04/15/2022

Resource-Constrained Neural Architecture Search on Tabular Datasets

The best neural architecture for a given machine learning problem depend...

0 Chengrun Yang, et al. ∙

∙ 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, ...

0 Chengrun Yang, et al. ∙

∙ 01/01/2021

TenIPS: Inverse Propensity Sampling for Tensor Completion

Tensors are widely used to represent multiway arrays of data. The recove...

0 Chengrun Yang, et al. ∙

∙ 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 ...

10 Jicong Fan, et al. ∙

∙ 06/07/2020

Efficient AutoML Pipeline Search with Matrix and Tensor Factorization

Data scientists seeking a good supervised learning model on a new datase...

0 Chengrun Yang, et al. ∙

∙ 05/04/2020

Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering

Low dimensional nonlinear structure abounds in datasets across computer ...

62 Jicong Fan, et al. ∙

∙ 08/09/2018

OBOE: Collaborative Filtering for AutoML Initialization

Algorithm selection and hyperparameter tuning remain two of the most cha...

0 Chengrun Yang, et al. ∙

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