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PAC learning

Probably Approximately Correct (PAC) learning analyzes machine learning mathematically using probability bounds.

Papers

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Showing 261–270 of 289 papers

TitleStatusHype
Efficient PAC Learning from the Crowd—0
On the Power of Learning from k-Wise Queries—0
Multi-step learning and underlying structure in statistical models—0
Predicting with Distributions—0
Simultaneous Private Learning of Multiple Concepts—0
Fast Collaborative Filtering from Implicit Feedback with Provable Guarantees—0
PAC Learning-Based Verification and Model Synthesis—0
Hardness of Online Sleeping Combinatorial Optimization Problems—0
The Optimal Sample Complexity of PAC Learning—0
Order-Revealing Encryption and the Hardness of Private Learning—0
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