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Skip to Search Results- 3Pruning
- 1Active Learning
- 1Attribute Selection
- 1Binary networks
- 1Cost Optimization
- 1Cost-Efficient Decision Tree
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Fall 2021
We study the problem of set discovery where given a few example tuples of a desired set, we want to find the set in a collection of sets. A challenge is that the example tuples may not uniquely identify a set, and a large number of candidate sets may be returned. Our focus is on interactive...
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Spring 2011
The goal of top-k ranking is to rank individuals so that the best k of them can be determined. Depending on the application domain, an individual can be a person, a product, an event, or just a collection of data or information for which an ordering makes sense. In the context of databases, top-k...
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Fall 2023
Oftentimes, machine learning applications using neural networks involve solving discrete optimization problems, such as in pruning, parameter-isolation-based continual learning and training of binary networks. Still, these discrete problems are combinatorial in nature and are also not amenable to...