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RESEARCH OF APPROACHES TO TEACHING THE COURSE “ALGORITHMS AND DATA STRUCTURES” FOR COMPUTER SCIENCE STUDENTS

Scientific notes of Taurida National V.I. Vernadsky University. Series: Technical Sciences, 2021
Yu.V. Prokop, O.H. Trofymenko, O.V. Dykyi   +2 more
openaire   +2 more sources

An Open Guide to Data Structures and Algorithms [PDF]

, 2023
This textbook serves as a gentle introduction for undergraduates to theoretical concepts in data structures and algorithms in computer science while providing coverage of practical implementation (coding) issues.
Bible, Paul W., Moser, Lucas
core   +2 more sources

Recursive Combinatorial Structures: Enumeration, Probabilistic Analysis and Random Generation [PDF]

, 2018
In a probabilistic context, the main data structures of computer science are viewed as random combinatorial objects. Analytic Combinatorics, as described in the book by Flajolet and Sedgewick, provides a set of high-level tools for their probabilistic
Salvy, Bruno
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A Direct Manipulation Language for Explaining Algorithms [PDF]

, 2014
Instructors typically explain algorithms in computer science by tracing their behavior, often on blackboards, sometimes with algorithm visualizations.
Davis, Randall, Guo, Philip J., Scott, Jeremy   +2 more
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Research and Education in Computational Science and Engineering [PDF]

, 2016
Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the ...
Biros, George, Bungartz, Hans, Corones, James, Cramer, Evin, Crowley, James, De Sterck, Hans, Ghattas, Omar, Gunzburger, Max, Hanke, Michael, Harrison, Robert, Heroux, Michael, Hesthaven, Jan, Jimack, Peter, Johnson, Chris, Jordan, Kirk E., Keyes, David E., Krause, Rolf, Kumar, Vipin, Mayer, Stefan, McInnes, Lois Curfman, Meza, Juan, Mørken, Knut Martin, Oden, J. Tinsley, Petzold, Linda, Raghavan, Padma, Rüde, Ulrich, Shontz, Suzanne M., Trefethen, Anne, Turner, Peter, Voevodin, Vladimir, Willcox, Karen, Wohlmuth, Barbara, Woodward, Carol S.   +32 more
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Chemoinformatics Research at the University of Sheffield: A History and Citation Analysis [PDF]

, 2003
This paper reviews the work of the Chemoinformatics Research Group in the Department of Information Studies at the University of Sheffield, focusing particularly on the work carried out in the period 1985-2002.
Bishop, N., Gillet, V.J., Holliday, J.D., Willett, P.   +3 more
core   +1 more source

Curriculum Guidelines for Undergraduate Programs in Data Science [PDF]

, 2017
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science.
Agarwal, Mahesh, Averett, Maia, Baumer, Benjamin, Bray, Andrew, Bressoud, Thomas, Bryant, Lance, Cheng, Lei, De Veaux, Richard, Francis, Amanda, Gould, Robert, Kim, Albert Y., Kretchmar, Matt, Lu, Qin, Moskol, Ann, Nolan, Deborah, Pelayo, Roberto, Raleigh, Sean, Sethi, Ricky J., Sondjaja, Mutiara, Tiruviluamala, Neelesh, Uhlig, Paul, Washington, Talitha, Wesley, Curtis, White, David, Ye, Ping   +24 more
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Evolving structure-function mappings in cognitive neuroscience using genetic programming [PDF]

, 2005
A challenging goal of psychology and neuroscience is to map cognitive functions onto neuroanatomical structures. This paper shows how computational methods based upon evolutionary algorithms can facilitate the search for satisfactory mappings by ...
Gobet, F, Parker, A
core   +1 more source

Inductive queries for a drug designing robot scientist [PDF]

, 2010
It is increasingly clear that machine learning algorithms need to be integrated in an iterative scientific discovery loop, in which data is queried repeatedly by means of inductive queries and where the computer provides guidance to the experiments that ...
A. Lingas, C. Hansch, C.A. Lipinski, D.R. Jones, D.R. Jones, H. Blockeel, J. Matousek, L. Raedt De, R.D. King, R.D. King, T. Gärtner   +10 more
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On the enumeration of closures and environments with an application to random generation [PDF]

, 2019
Environments and closures are two of the main ingredients of evaluation in lambda-calculus. A closure is a pair consisting of a lambda-term and an environment, whereas an environment is a list of lambda-terms assigned to free variables.
Bendkowski, Maciej, Lescanne, Pierre
core   +3 more sources