Global ETD Search

On Principled Modeling of Inductive Bias in Machine Learning

Liu, WeiyangUniversity of Cambridge2024

… modeling, we introduce the iterative machine teaching framework for studying the effect of training data manipulation on inductive bias. Specifically, we consider two teaching scenarios: (1) label synthesis teaching: given data points, the teacher model adaptively synthesizes its …

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Randomized Algorithms for Mega-AI Models

Xu, ZhaozhuoRice University2023

… we have witnessed remarkable accomplishments in machine learning (ML) models due to increases in their sizes. However, the growth in model size has outpaced upgrades to hardware and network bandwidth, resulting in difficulties in training these Mega-AI models within current system …

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Optimizing the wisdom of the crowd: Learning, teaching, and recommendation

Zhou, YaoUniversity of Illinois at Urbana-Champaign2022

Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms

uiuc Repository record for Optimizing the wisdom of the crowd: Learning, teaching, and recommendation (opens in a new tab)

Modele ewaluacji poprawności danych lingwistycznych pozyskanych metodą crowdsourcing

Włodarczyk, Wojciech2023

amu-pl