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University of Illinois Urbana-Champaign

A linear constraint driven approach to efficiently enhancing branch and bound in neural network verification

dc:creator Chavez, Jorge

thesis:degree_name M.S.

dc:date2025

Abstract

dc:description

Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms

Degree

thesis:*

Name thesis:degree_name: M.S.
Level thesis:degree_level: Thesis
Discipline thesis:degree_discipline: Electrical & Computer Engr
Grantor: University of Illinois Urbana-Champaign
Year dc:date: 2025

Author and committee

dc:creator, dc:contributor.*

Author dc:creator: Chavez, Jorge
Contributors dc:contributor: Zhang, Huan

Subjects

dc:subject × 2

Rights

dc:rights

Statement dc:rights: Copyright 2025 Jorge Chavez
Language dc:language: en, eng

Identifiers

dc:identifier.*

Handle dc:identifier: https://hdl.handle.net/2142/129353
OAI identifier oai:identifier: oai:www.ideals.illinois.edu:2142/129353

Chain of custody

source

Harvested from: University of Illinois - Urbana-Champaign
Base URL: www.ideals.illinois.edu/oai-pmh
Last updated: 2026-07-22
Source record: OAI-PMH GetRecord

related terms

citation

Chavez, Jorge. A linear constraint driven approach to efficiently enhancing branch and bound in neural network verification. Thesis thesis, University of Illinois Urbana-Champaign, 2025. https://hdl.handle.net/2142/129353

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