Topic Brief: An important theme in theoretical computer science over the last decade has been the usefulness of translating a combinatorial ... Authors: Shuichi Hirahara (National Institute of Informatics); Mikito Nanashima (Tokyo Institute of Technology) ITCS - Innovations ...

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Authors: Shuichi Hirahara (National Institute of Informatics); Mikito Nanashima (Tokyo Institute of Technology) ITCS - Innovations ... An important theme in theoretical computer science over the last decade has been the usefulness of translating a combinatorial ...

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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 ... Russell Impagliazzo (UC San Diego) Simons Institute 10th Anniversary Symposium.

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  • 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 ...
  • Authors: Shuichi Hirahara (National Institute of Informatics); Mikito Nanashima (Tokyo Institute of Technology) ITCS - Innovations ...
  • Russell Impagliazzo (UC San Diego) Simons Institute 10th Anniversary Symposium.
  • An important theme in theoretical computer science over the last decade has been the usefulness of translating a combinatorial ...

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Connections Between Pseudorandomness and Machine Learning

Connections Between Pseudorandomness and Machine Learning

Russell Impagliazzo (UC San Diego) Simons Institute 10th Anniversary Symposium.

Learning versus Pseudorandom Generators in Constant Parallel Time

Learning versus Pseudorandom Generators in Constant Parallel Time

Authors: Shuichi Hirahara (National Institute of Informatics); Mikito Nanashima (Tokyo Institute of Technology) ITCS - Innovations ...

Pseudorandomness in Data Structures

Pseudorandomness in Data Structures

Read more details and related context about Pseudorandomness in Data Structures.

Fundamental Techniques in Pseudorandomness I

Fundamental Techniques in Pseudorandomness I

Read more details and related context about Fundamental Techniques in Pseudorandomness I.

Threshold Functions: Approximation, Pseudorandomness and Learning

Threshold Functions: Approximation, Pseudorandomness and Learning

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 ...

The Power of Distinguishing Simple From Random (Part I)

The Power of Distinguishing Simple From Random (Part I)

Read more details and related context about The Power of Distinguishing Simple From Random (Part I).

Learning Versus Pseudorandom Generators in Constant Parallel Time

Learning Versus Pseudorandom Generators in Constant Parallel Time

Read more details and related context about Learning Versus Pseudorandom Generators in Constant Parallel Time.

Limit Theorems in Pseudorandomness and Learning Theory

Limit Theorems in Pseudorandomness and Learning Theory

An important theme in theoretical computer science over the last decade has been the usefulness of translating a combinatorial ...

Pseudorandomness When the Odds Are Against You

Pseudorandomness When the Odds Are Against You

Ronen Shaltiel, University of Haifa Expanders and Extractors.

What Are Skip Connections ResNets and Why Do They Work

What Are Skip Connections ResNets and Why Do They Work

Read more details and related context about What Are Skip Connections ResNets and Why Do They Work.