by instadatahelp | Aug 31, 2023 | AI Blogs
Fundamental Limits and Algorithms for Sparse Linear Regression with Sublinear Sparsity Lan V. Truong; 24(64):1−49, 2023. Abstract In this study, we investigate the normalized mutual information and minimum mean-square-error (MMSE) of sparse linear regression in the...
![Predicting Online Job Failures in an HPC System Using an HPC System (arXiv:2308.15481v1 [cs.DC])](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Aug 31, 2023 | AI Blogs
High Performance Computing (HPC) systems have become increasingly complex and have significant impacts on the economy and society. However, their high energy consumption is a critical issue in the face of environmental and energy crises. Therefore, it is crucial to...
by instadatahelp | Aug 31, 2023 | AI Blogs
LibMTL: A Python Library for Deep Multi-Task Learning Authors: Baijiong Lin, Yu Zhang; Published in Journal of Machine Learning Research, 24(209):1−7, 2023. Abstract This article introduces LibMTL, a Python library based on PyTorch that offers a comprehensive,...
by instadatahelp | Aug 31, 2023 | AI Blogs
In this study, we address the challenge of using machine learning to predict individual treatment effects (ITEs). Previous research has focused on developing machine learning models that can estimate the conditional average treatment effect (CATE). These models...
by instadatahelp | Aug 30, 2023 | AI Blogs
Distributed Nonparametric Regression Imputation for Missing Response Problems with Large-scale Data Ruoyu Wang, Miaomiao Su, Qihua Wang; 24(68):1−52, 2023. Abstract Missing data analysis often employs nonparametric regression imputation, but this approach faces...
by instadatahelp | Aug 30, 2023 | AI Blogs
Current image models typically use a two-stage approach: pre-training on large datasets and then fine-tuning using cross-entropy loss. However, studies have shown that cross-entropy loss may not provide optimal generalization and stability. Although supervised...
