518. OR - More Than Just Optimisation
Invited abstract in session TB-34: Advancements of OR-analytics in statistics, machine learning and data science 3, stream Advancements of OR-analytics in statistics, machine learning and data science.
Tuesday, 10:30-12:00Room: Michael Sadler LG10
Authors (first author is the speaker)
| 1. | Joseph Brennan
|
| Technical, Wolfram | |
| 2. | Jon McLoone
|
| Wolfram |
Abstract
Wolfram's vision of unified computation is a high-level programming language where any computation you might need is built in and designed to work together without the need for external libraries or programs. While this includes the full range of industrial scale optimization that would be in an OR tool, it extends to include Machine Learning, Time Series, and Image Analysis.
In this talk using live demos, we will show how you can produce new insights and support research workflows from computation through to deployment.
Furthermore having a unified design enables greater automation so OR Researchers can express problems at a higher level with less coding.
The talk will be illustrated with examples from many domains including manufacturing, transport and resource allocation, across computations in graph theory, linear and non-linear optimization and system modeling.
Keywords
- Machine Learning
- Computer Science/Applications
- Optimization Modeling
Status: accepted
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