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dateMore Than a Year Ago
subjectArtificial Intelligence
authorSanjeev Arora

From Communications of the ACM

Technical Perspective: Why Don't Today's Deep Nets Overfit to Their Training Data?

"Understanding Deep Learning (Still) Requires Rethinking Generalization," Chiyuan Zhang, et al., brings a fundamental new theoretical challenge: Why don't today's...

Learning Topic Models - Provably and Efficiently
From Communications of the ACM

Learning Topic Models - Provably and Efficiently

This article shows that some new theoretical algorithms that have provable guarantees can be adapted to yield highly practical tools for topic modeling.

Computational Complexity and Information Asymmetry in Financial Products
From Communications of the ACM

Computational Complexity and Information Asymmetry in Financial Products

Securitization of cash flows using financial derivatives transformed the financial industry over the last three decades. Derivatives...
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