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Mathematics

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Publication

SECURITY OF HOMOMORPHIC ENCRYPTION

Melissa Chase, Hao Chen, Jintai Ding, Shafi Goldwasser, Sergey Gorbunov, Jeffrey Hoffstein, Kristin Lauter, Satya Lokam, Dustin Moody, Travis Morrison, Amit Sahai, Vinod Vaikuntanathan

January 2018

Publication

Mean Field Residual Networks: On the Edge of Chaos

Greg Yang, Samuel S. Schoenholz

Neural Information Processing Systems (NIPS) 2017 | December 2017

Publication

Iterative Collaborative Filtering for Sparse Matrix Estimation

Christian Borgs, Jennifer Chayes, Christina E. Lee, Devavrat Shah

December 2017

December 2017

Publication

Rigorous Analysis of a Randomised Number Field Sieve

Jonathan Lee, Ramarathnam Venkatesan

Journal of Number Theory | December 2017, Vol 187: pp. 92-159

Publication

Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting

Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu

Advances in Neural Information Processing Systems | December 2017

Video

Optimal Safe Path Planning Using Polynomials: From Algebra to Geometry

November 27, 2017 | Nak-seung Patrick Hyun

Optimal Safe Path Planning Using Polynomials: From Algebra to Geometry

Video

Foundations of Data Science – Lecture 9 – Two Applications of SVD

November 15, 2017 | Ravi Kannan

Modern data often consists of feature vectors with a large number of features. High-dimensional geometry and Linear Algebra (Singular Value Decomposition) are two of the crucial areas which form the mathematical foundations of Data Science.…

Foundations of Data Science - Lecture 9 - Two Applications of SVD

Video

Foundations of Data Science – Lecture 8 – Low Rank Approximation (LRA) via Length Squared Sampling

November 13, 2017 | Ravi Kannan

Modern data often consists of feature vectors with a large number of features. High-dimensional geometry and Linear Algebra (Singular Value Decomposition) are two of the crucial areas which form the mathematical foundations of Data Science.…

Foundations of Data Science - Lecture 8 - Low Rank Approximation (LRA) via Length Squared Sampling

Video

Foundations of Data Science – Lecture 7 – Singular Value Decomposition – ll

November 8, 2017 | Ravi Kannan

Modern data often consists of feature vectors with a large number of features. High-dimensional geometry and Linear Algebra (Singular Value Decomposition) are two of the crucial areas which form the mathematical foundations of Data Science.…

Foundations of Data Science - Lecture 7 - Singular Value Decomposition - ll

Video

Foundations of Data Science – Lecture 6 – Singular Value Decomposition – l

November 6, 2017 | Ravi Kannan

Modern data often consists of feature vectors with a large number of features. High-dimensional geometry and Linear Algebra (Singular Value Decomposition) are two of the crucial areas which form the mathematical foundations of Data Science.…

Foundations of Data Science - Lecture 6 - Singular Value Decomposition - l

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