<--- Back to Details
First PageDocument Content
Western China / Geography of New York / James Endicott / Chengdu / Sichuan / Endicott /  New York / York University / Toronto / Geography of the United States / Project 211 / Project 985 / Sichuan University
Date: 2012-10-14 06:06:48
Western China
Geography of New York
James Endicott
Chengdu
Sichuan
Endicott
New York
York University
Toronto
Geography of the United States
Project 211
Project 985
Sichuan University

Microsoft Word - ShortRsume2011.rtf

Add to Reading List

Source URL: www.yorku.ca

Download Document from Source Website

File Size: 28,16 KB

Share Document on Facebook

Similar Documents

Theoretical computer science / Mathematics / Computational complexity theory / Logic in computer science / NP-complete problems / Electronic design automation / Formal methods / Constraint programming / Satisfiability modulo theories / Boolean satisfiability problem / Solver / Automated reasoning

Outline SMT: Where Do We Go From Here? Clark Barrett, New York University SMT Workshop, July 17, 2014

DocID: 1xW2J - View Document

Model theory / Mathematics / Metalogic / Logic / Mathematical logic / Interpretation / Structure

Sharing is Caring: Combination of Theories? Dejan Jovanovi´c and Clark Barrett New York University Abstract. One of the main shortcomings of the traditional methods for combining theories is the complexity of guessing t

DocID: 1xVl2 - View Document

Computer programming / Software engineering / Declarative programming / Recursion / Functional programming / Computability theory / Theoretical computer science / Programming paradigms / Algebraic data type / Fold / Pattern matching / Conditional

Unfailing Haskell: A Static Checker for Pattern Matching Neil Mitchell and Colin Runciman http://www.cs.york.ac.uk/∼ndm , http://www.cs.york.ac.uk/∼colin University of York, UK

DocID: 1xVgx - View Document

Learning / Education / Human behavior / Educational psychology / Educational practices / Philosophy of education / Curricula / Bayesian network / Active learning / Question / Bayesian inference / Machine learning

Asking and evaluating natural language questions Anselm Rothe1 , Brenden M. Lake2 , and Todd M. Gureckis1 1 Department of Psychology, 2 Center for Data Science, New York University

DocID: 1xVcW - View Document

Artificial neural networks / Computational neuroscience / Artificial intelligence / Learning / Applied mathematics / Machine learning / Computational statistics / Computer vision / Convolutional neural network / Deep learning / Concept learning / One-shot learning

Learning Inductive Biases with Simple Neural Networks Reuben Feinman () Center for Neural Science New York University Abstract People use rich prior knowledge about the world in order to

DocID: 1xV8d - View Document