OAMIP: optimizing ANN architectures using mixed-integer programming

DOI10.1007/978-3-031-33271-5_15arXiv2002.07259OpenAlexW4377231357MaRDI QIDQ6057263

Margarida Carvalho, Mostafa ElAraby, Guy Wolf

Publication date: 4 October 2023

Published in: Integration of Constraint Programming, Artificial Intelligence, and Operations Research (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2002.07259

zbMATH Keywords

mixed integer programmingsparse neural networksneurons rankingpruning neural networks

Mathematics Subject Classification ID

Combinatorial optimization (90C27) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Operations research and management science (90Bxx)

Related Items (1)

Deep Neural Networks Pruning via the Structured Perspective Regularization

Cites Work

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• Deep neural networks and mixed integer linear optimization
• Lossless compression of deep neural networks
• CVXPY: A Python-Embedded Modeling Language for Convex Optimization
• Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2D and 3D Images
• Strong mixed-integer programming formulations for trained neural networks

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