Understanding Connections Between Pseudorandomness And Machine Learning
Exploring Connections Between Pseudorandomness And Machine Learning reveals several interesting facts. Russell Impagliazzo (UC San Diego) Simons Institute 10th Anniversary Symposium.
Key Takeaways about Connections Between Pseudorandomness And Machine Learning
- Luca Trevisan, UC Berkeley https://simons.berkeley.edu/talks/fundamental-techniques-in-
- An important theme in theoretical computer science over the last decade has been the usefulness of translating a combinatorial ...
- Rachel (Huijia) Lin (University of Washington) ...
- Omer Reingold, Stanford University https://simons.berkeley.edu/talks/omer-reingold-2017-03-06 Proving and Using ...
- Abstract: A degree-d threshold function is a boolean function of the form f(x) = sign(p(x)), where p(x) is a degree-d polynomial over ...
Detailed Analysis of Connections Between Pseudorandomness And Machine Learning
Valentine Kabanets (Simon Fraser University) https://simons.berkeley.edu/talks/power-distinguishing-simple-random-part-i ... Authors: Shuichi Hirahara (National Institute of Informatics); Mikito Nanashima (Tokyo Institute of Technology) ITCS - Innovations ... Explicit SoS lower bounds from high-dimensional expanders Irit Dinur (Weizmann Institute of Science), Yuval Filmus (Technion), ...
Mikito Nanashima (Tokyo Institute of Technology) ...
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