Results 1 to 10 of about 2,631,463 (266)

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

open access: goldScientific notes of Taurida National V.I. Vernadsky University. Series: Technical Sciences, 2021
Yuliia Prokop   +2 more
openalex   +2 more sources

Unmasking the giant: A comprehensive evaluation of ChatGPT's proficiency in coding algorithms and data structures [PDF]

open access: yesInternational Conference on Agents and Artificial Intelligence, 2023
The transformative influence of Large Language Models (LLMs) is profoundly reshaping the Artificial Intelligence (AI) technology domain. Notably, ChatGPT distinguishes itself within these models, demonstrating remarkable performance in multi-turn ...
Sayed Erfan Arefin   +4 more
semanticscholar   +1 more source

ChatGPT Participates in a Computer Science Exam [PDF]

open access: yesarXiv.org, 2023
We asked ChatGPT to participate in an undergraduate computer science exam on ''Algorithms and Data Structures''. The program was evaluated on the entire exam as posed to the students.
Sebastian Bordt, U. V. Luxburg
semanticscholar   +1 more source

Studied Questions in Data Structures and Algorithms Assessments

open access: yesAnnual Conference on Innovation and Technology in Computer Science Education, 2023
Designing a proper exam that accurately evaluates students' knowledge and skills is one of the important tasks of every teacher. The format of the exams affects the way students learn throughout the course, and a well-designed exam can enhance meaningful
I. Gaber, Amir Kirsh, D. Statter
semanticscholar   +1 more source

An Open Guide to Data Structures and Algorithms [PDF]

open access: yes, 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

Computational identification of protein-coding sequences by comparative analysis [PDF]

open access: yesInternational Journal of Data Mining and Bioinformatics, 2007
Gene prediction is an essential step in understanding the genome of a species once it has been sequenced. For that, a promising direction in current research on gene finding is a comparative genomics approach. In this paper, we present a novel approach to identifying evolutionarily conserved protein-coding sequences in genomes.
Wu, Feihong   +3 more
openaire   +19 more sources

Insilico Analysis of RHES Protein for Huntington's Disease [PDF]

open access: yes, 2023
There are numerous subfields within tree science, including biotechnology, zoology, and botany. One of the newest developments in science is the discipline of bioinformatics, which is one of the fields that is booming right now.
Aruna S. I, Dr. Manu Philip, Dr. Showmy Reshin, Jyothi C J, Chinchu K, Marymol Shajan
core   +3 more sources

A structural optimization algorithm with stochastic forces and stresses [PDF]

open access: yesNat. Comput. Sci. 2, 736-744 (2022), 2022
We propose an algorithm for optimizations in which the gradients contain stochastic noise. This arises, for example, in structural optimizations when computations of forces and stresses rely on methods involving Monte Carlo sampling, such as quantum Monte Carlo or neural network states, or are performed on quantum devices which have intrinsic noise ...
arxiv   +1 more source

Algorithm Engineering for fundamental Sorting and Graph Problems [PDF]

open access: yes, 2014
Fundamental Algorithms build a basis knowledge for every computer science undergraduate or a professional programmer. It is a set of basic techniques one can find in any (good) coursebook on algorithms and data structures.
Osipov, Vitaly
core   +2 more sources

Cross Tensor Approximation Methods for Compression and Dimensionality Reduction [PDF]

open access: yes, 2021
Cross Tensor Approximation (CTA) is a generalization of Cross/skeleton matrix and CUR Matrix Approximation (CMA) and is a suitable tool for fast low-rank tensor approximation.
Ahmadi Asl, Salman   +6 more
core   +2 more sources

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