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Neuro-symbolic learning was proposed to address challenges with training neural networks for complex reasoning tasks with the added benefits of interpretability, reliability, and efficiency. Neuro-symbolic learning methods traditionally…

Machine Learning · Computer Science 2025-06-02 Adam Stein , Aaditya Naik , Neelay Velingker , Mayur Naik , Eric Wong

The most common method to auto-grade a student's submission in a CS1 or a CS2 course is to run it against a pre-defined test suite and compare the results against reference results. However, this technique cannot be used if the correctness…

Artificial Intelligence · Computer Science 2024-10-22 Aaryen Mehta , Gagan Aryan

A natural way of increasing our understanding of NP-complete graph problems is to restrict the input to a special graph class. Classes of $H$-free graphs, that is, graphs that do not contain some graph $H$ as an induced subgraph, have…

Data Structures and Algorithms · Computer Science 2022-04-19 Christoph Brause , Petr Golovach , Barnaby Martin , Daniël Paulusma , Siani Smith

In this paper, a low-complexity approach for the automorphism ensemble decoder (AED) using successive cancellation (SC) as constituent decoders is proposed. The approach sequentially activates sub-decoders and terminates the decoding…

Information Theory · Computer Science 2026-05-21 Charles Pillet , Pascal Giard , Bassant Selim , François Leduc-Primeau

Although whether P equals NP is an important, open problem in computer science, and although Jaeger's 2008 paper, "Solving the P/NP Problem Under Intrinsic Uncertainty" (arXiv:0811.0463) presents an attempt at tackling the problem by…

Computational Complexity · Computer Science 2009-04-27 Andrew Keenan Richardson , Cole Arthur Brown

Neural program embedding can be helpful in analyzing large software, a task that is challenging for traditional logic-based program analyses due to their limited scalability. A key focus of recent machine-learning advances in this area is…

Machine Learning · Computer Science 2019-05-29 Ke Wang , Mihai Christodorescu

Convolutional neural networks (CNNs) have been successfully applied to many recognition and learning tasks using a universal recipe; training a deep model on a very large dataset of supervised examples. However, this approach is rather…

Machine Learning · Statistics 2018-06-04 Ozan Sener , Silvio Savarese

Robin Hirsch posed in 1996 the 'Really Big Complexity Problem': classify the computational complexity of the network satisfaction problem for all finite relation algebras A. We provide a complete classification for the case that A is…

Logic · Mathematics 2023-01-06 Manuel Bodirsky , Simon Knäuer

In Petri net synthesis we ask whether a given transition system $A$ can be implemented by a Petri net $N$. Depending on the level of accuracy, there are three ways how $N$ can implement $A$: an embedding, the least accurate implementation,…

Formal Languages and Automata Theory · Computer Science 2023-06-22 Raymond Devillers , Ronny Tredup

The growing number of students enrolling in Computer Science (CS) programmes is pushing CS educators to their limits. This poses significant challenges to computing education, particularly the teaching of introductory programming and…

Software Engineering · Computer Science 2024-12-19 Zhiyu Fan , Yannic Noller , Ashish Dandekar , Abhik Roychoudhury

This paper presents a comprehensive study to efficiently build named entity recognition (NER) systems when a small number of in-domain labeled data is available. Based upon recent Transformer-based self-supervised pre-trained language…

Computation and Language · Computer Science 2021-01-01 Jiaxin Huang , Chunyuan Li , Krishan Subudhi , Damien Jose , Shobana Balakrishnan , Weizhu Chen , Baolin Peng , Jianfeng Gao , Jiawei Han

Open-ended programming increases students' motivation by allowing them to solve authentic problems and connect programming to their own interests. However, such open-ended projects are also challenging, as they often encourage students to…

Human-Computer Interaction · Computer Science 2021-04-27 Wengran Wang , Archit Kwatra , James Skripchuk , Neeloy Gomes , Alexandra Milliken , Chris Martens , Tiffany Barnes , Thomas Price

In the last years many results in the area of semidefinite programming were obtained for invariant (finite dimensional, or infinite dimensional) semidefinite programs - SDPs which have symmetry. This was done for a variety of problems and…

Optimization and Control · Mathematics 2019-11-07 Christine Bachoc , Dion C. Gijswijt , Alexander Schrijver , Frank Vallentin

Semiring algebras have been shown to provide a suitable language to formalize many noteworthy combinatorial problems. For instance, the Shortest-Path problem can be seen as a special case of the Algebraic-Path problem when applied to the…

Computational Complexity · Computer Science 2025-12-04 Ambroise Baril , Miguel Couceiro , Victor Lagerkvist

Open sets are central to mathematics, especially analysis and topology, in ways few notions are. In most, if not all, computational approaches to mathematics, open sets are only studied indirectly via their 'codes' or 'representations'. In…

Logic · Mathematics 2024-08-15 Dag Normann , Sam Sanders

This is a survey of recent progress in several areas of combinatorial algebra. We consider combinatorial problems about free groups, polynomial algebras, free associative and Lie algebras. Our main idea is to study automorphisms and, more…

Group Theory · Mathematics 2016-09-07 Alexander A. Mikhalev , Vladimir Shpilrain , Jie-Tai Yu

We consider a natural generalization of Vertex Cover: the Subset Vertex Cover problem, which is to decide for a graph $G=(V,E)$, a subset $T\subseteq V$ and integer $k$, if $V$ has a subset $S$ of size at most $k$, such that $S$ contains at…

Program errors can occur in any type of programming, and can manifest in a variety of ways, such as unexpected output, crashes, or performance issues. And program error diagnosis can often be too abstract or technical for developers to…

Software Engineering · Computer Science 2025-01-07 Zhenyu Xu , Victor S. Sheng

Phase transitions in combinatorial problems have recently been shown to be useful in locating "hard" instances of combinatorial problems. The connection between computational complexity and the existence of phase transitions has been…

Computational Complexity · Computer Science 2016-11-17 Gabriel Istrate

In this paper we study the parameterized complexity of two well-known permutation group problems which are NP-complete. 1. Given a permutation group G=<S>, subgroup of $S_n$, and a parameter $k$, find a permutation $\pi$ in G such that…

Computational Complexity · Computer Science 2013-01-18 Vikraman Arvind
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