Optimization of sparsity-constrained neural networks as a mixed integer linear program
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Publication:6145048
DOI10.1007/s10957-023-02317-xOpenAlexW4387933920MaRDI QIDQ6145048
Publication date: 8 January 2024
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-023-02317-x
neural networksmixed integer linear programmingfeature selectionsparse networksresource optimization
Cites Work
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- Feature extraction. Foundations and applications. Papers from NIPS 2003 workshop on feature extraction, Whistler, BC, Canada, December 11--13, 2003. With CD-ROM.
- Logic and integer programming
- Deep neural networks and mixed integer linear optimization
- Optimization problems for machine learning: a survey
- Lossless compression of deep neural networks
- Between steps: intermediate relaxations between big-M and convex hull formulations
- Mathematical Programming in Neural Networks
- 10.1162/153244303322753616
- JANOS: An Integrated Predictive and Prescriptive Modeling Framework
- A logical calculus of the ideas immanent in nervous activity
- Strong mixed-integer programming formulations for trained neural networks
- Principled deep neural network training through linear programming
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