51 lines
2.0 KiB
Markdown
51 lines
2.0 KiB
Markdown
---
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authors:
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- "Dutta, Souradeep"
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- "Jha, Susmit"
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- "Sankaranarayanan, Sriram"
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- "Tiwari, Ashish"
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- "Dutle, Aaron"
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- "Muñoz, César"
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- "Narkawicz, Anthony"
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citekey: "duttaOutputRangeAnalysis2018"
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publish_date: 2018-01-01
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publisher: "Springer International Publishing"
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location: "Cham"
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pages: 121-138
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last_import: 2025-05-12
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---
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# Indexing Information
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Published: 2018-01
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**DOI**
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[10.1007/978-3-319-77935-5_9](https://doi.org/10.1007/978-3-319-77935-5_9)
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**ISBN**
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[978-3-319-77935-5](https://www.isbnsearch.org/isbn/978-3-319-77935-5)
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#ToRead
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>[!Abstract]
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>Given a neural network (NN) and a set of possible inputs to the network described by polyhedral constraints, we aim to compute a safe over-approximation of the set of possible output values. This operation is a fundamental primitive enabling the formal analysis of neural networks that are extensively used in a variety of machine learning tasks such as perception and control of autonomous systems. Increasingly, they are deployed in high-assurance applications, leading to a compelling use case for formal verification approaches. In this paper, we present an efficient range estimation algorithm that iterates between an expensive global combinatorial search using mixed-integer linear programming problems, and a relatively inexpensive local optimization that repeatedly seeks a local optimum of the function represented by the NN. We implement our approach and compare it with Reluplex, a recently proposed solver for deep neural networks. We demonstrate applications of our approach to computing flowpipes for neural network-based feedback controllers. We show that the use of local search in conjunction with mixed-integer linear programming solvers effectively reduces the combinatorial search over possible combinations of active neurons in the network by pruning away suboptimal nodes.>[!seealso] Related Papers
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>
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# Annotations
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## Notes
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![[Paper Notes/Output Range Analysis for Deep Feedforward Neural Networks.md]]
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## Highlights From Zotero
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## Follow-Ups
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