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#### 1Courses for Numerical Sampling and Inference

Courses for Numerical Sampling and Inference at Duke
3 years ago by @kirk86
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#### 1Computational Statistics in Python

Computational Statistics in Python Course
3 years ago by @kirk86
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#### 1Courses By Michael Jordan

Courses into CS and Stats
3 years ago by @kirk86
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#### 1Topics in Theoretical Computer Science: An Algorithmist's Toolkit

Topics in Theoretical Computer Science: An Algorithmist's Toolkit 2007
3 years ago by @kirk86
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#### 1Topics in Theoretical Computer Science

Topics in Theoretical Computer Science
3 years ago by @kirk86
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#### 1Theoretical Computer Science

3 years ago by @kirk86
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#### 1Mathematics of CS

Mathematics of CS MIT 6.042 Spring 2018
3 years ago by @kirk86
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#### 1Building Blocks for Theoretical Computer Science

Building Blocks for Theoretical Computer Science
3 years ago by @kirk86
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#### 2Algorithms by Jeff Erickson

Algorithms by Jeff Erickson
3 years ago by @kirk86
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#### 1Luca Trevisan Lecture Notes on Theoretical CS and ML

Luca Trevisan Lecture Notes on Theoretical CS, ML and Optim
4 years ago by @kirk86
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#### 1Lecture Notes | in theory

4 years ago by @kirk86
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#### 1Mathematics for Computer Science | Electrical Engineering and Computer Science | MIT OpenCourseWare

This subject offers an interactive introduction to discrete mathematics oriented toward computer science and engineering. The subject coverage divides roughly into thirds: Fundamental concepts of mathematics: Definitions, proofs, sets, functions, relations. Discrete structures: graphs, state machines, modular arithmetic, counting. Discrete probability theory. On completion of 6.042J, students will be able to explain and apply the basic methods of discrete (noncontinuous) mathematics in computer science. They will be able to use these methods in subsequent courses in the design and analysis of algorithms, computability theory, software engineering, and computer systems.Interactive site components can be found on the Unit pages in the left-hand navigational bar, starting with Unit 1: Proofs.
4 years ago by @kirk86
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#### 1CS-121 / CSCI-E121: Introduction to Theoretical Computer Science :: CS 121 Website

Introduction to Theoretical Computer Science - Harvard CS Concentration
4 years ago by @kirk86
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#### 1Introduction to Theoretical Computer Science

Barak, Boaz
4 years ago by @kirk86
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#### 16.045/18.400 Materials Theoretical Computer Sciece

Theoretical Computer Science Notes from MIT
4 years ago by @kirk86
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#### 115-251 Spring 2019 Theoretical Computer Science

Theoretical Computer Science from CMU
4 years ago by @kirk86
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#### 1Numerical Solution of Fuzzy Differential Equations By Milne's Predictor-Corrector Method and the Dependency Problem

K. K, I. S, and M. S. Applied Mathematics and Sciences: An International Journal (MathSJ) 1 (2): 65-74 (August 2014)
a year ago by @journalmathsj
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#### 1Precise Attitude Determination Using a Hexagonal GPS Platform

A. Arsenault, and S. Sud. Signal Processing: An International Journal (SPIJ) 14 (1): 1-14 (October 2021)
2 years ago by @cscjournals
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#### 1IR-Tree Implementation using Index Document Search Method

D. Kanthale, and R.P.Mahajan. International Journal of Innovative Science and Modern Engineering (IJISME) 2 (7): 11-15 (June 2014)
2 years ago by @ijisme_beiesp
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#### 1Securing Privacy of Data in E-Marketing Against Malicious User

S. Jadhao, and S. Bhonde. International Journal of Innovative Science and Modern Engineering (IJISME) 3 (8): 1-5 (July 2015)
2 years ago by @ijisme_beiesp
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#### 1Syntax and Semantics for Cinnamon Programming

International Journal of Computer Science and Information Technology (IJCSIT) 9 (5): 127 - 150 (October 2017)
2 years ago by @shamerjose
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#### 3A Class of Models with the Potential to Represent Fundamental Physics

(2020)cite arxiv:2004.08210.
3 years ago by @vgivanovic
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#### 1Toward A Computational Theory of Everything

International Journal of Recent advances in Physics (IJRAP) 9 (3): 20 (August 2020)
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#### 2Approximate Bayesian computation via the energy statistic

H. Nguyen, J. Arbel, H. Lü, and F. Forbes. IEEE Access (2020)
3 years ago by @kirk86
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#### 3Reducibility and Statistical-Computational Gaps from Secret Leakage

M. Brennan, and G. Bresler. (2020)cite arxiv:2005.08099Comment: 175 pages; subsumes preliminary draft arXiv:1908.06130; accepted for presentation at the Conference on Learning Theory (COLT) 2020.
3 years ago by @kirk86
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#### 2The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure

(2018)cite arxiv:1809.03063.
3 years ago by @kirk86
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#### 2Computational Concentration of Measure: Optimal Bounds, Reductions, and More

(2019)cite arxiv:1907.05401.
3 years ago by @kirk86
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#### 7The Transitive Reduction of a Directed Graph.

A. Aho, M. Garey, and J. Ullman. SIAM J. Comput. 1 (2): 131-137 (1972)
3 years ago by @tom.hanika
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#### 2Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation

(2019)cite arxiv:1910.04920Comment: AISTATS, 2020.
3 years ago by @kirk86
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#### 4A Theory of Usable Information Under Computational Constraints

Y. Xu, S. Zhao, J. Song, R. Stewart, and S. Ermon. (2020)cite arxiv:2002.10689Comment: ICLR 2020 (Talk).
3 years ago by @kirk86
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#### 1Probabilistic Analysis of Learning in Artificial Neural Networks: The PAC Model and its Variants

Neural Computing Surveys (1997)
3 years ago by @kirk86
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#### 2Formal Concept Analysis on Graphics Hardware.

W. Langdon, S. Yoo, and M. Harman. CLA , volume 959 of CEUR Workshop Proceedings, page 413-416. CEUR-WS.org, (2011)
3 years ago by @tomhanika
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