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Related papers: Blind graph rewriting systems

200 papers

In this paper, we are interested in memoryless computation, a modern paradigm to compute functions which generalises the famous XOR swap algorithm to exchange the contents of two variables without using a buffer. This uses a combinatorial…

Computational Complexity · Computer Science 2015-03-19 Maximilien Gadouleau , Soren Riis

We define a compilation scheme for a constructor-based, strongly-sequential, graph rewriting system which shortcuts some needed steps. The object code is another constructor-based graph rewriting system. This system is normalizing for the…

Programming Languages · Computer Science 2015-05-28 Sergio Antoy , Jacob Johannsen , Steven Libby

Here, we introduce a new class of computer which does not use any circuit or logic gate. In fact, no program needs to be written: it learns by itself and writes its own program to solve a problem. Godels incompleteness argument is explored…

Emerging Technologies · Computer Science 2014-01-30 Subrata Ghosh , Krishna Aswani , Surabhi Singh , Satyajit Sahu , Daisuke Fujita , Anirban Bandyopadhyay

We introduce a simple initial working system in which relations (such as part-whole) are directly represented via an architecture with operating and learning rules fundamentally distinct from standard artificial neural network methods.…

Machine Learning · Computer Science 2026-02-06 E Bowen , R Granger , A Rodriguez

Blind Quantum Computation lets a limited-capability client delegate its complex computation to a remote server without revealing its data or computation. Several such protocols have been proposed under varied quantum computing models.…

Quantum Physics · Physics 2025-12-18 Mohit Joshi , Manoj Kumar Mishra , S. Karthikeyan

Adversarial attacks on graphs have attracted considerable research interests. Existing works assume the attacker is either (partly) aware of the victim model, or able to send queries to it. These assumptions are, however, unrealistic. To…

Machine Learning · Computer Science 2021-09-01 Jiarong Xu , Yizhou Sun , Xin Jiang , Yanhao Wang , Yang Yang , Chunping Wang , Jiangang Lu

While linear attention architectures offer efficient inference, compressing unbounded history into a fixed-size memory inherently limits expressivity and causes information loss. To address this limitation, we introduce Random Access Memory…

Machine Learning · Computer Science 2026-02-13 Kaicheng Xiao , Haotian Li , Liran Dong , Guoliang Xing

This article presents a signature-free distributed algorithm which builds an atomic read/write shared memory on top of an $n$-process asynchronous message-passing system in which up to $t<n/3$ processes may commit Byzantine failures. From a…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-28 Achour Mosteafoui , Matoula Petrolia , Michel Raynal , Claude Jard

Universal QRAM (U-QRAM) is a fixed, data-independent unitary interface that implements coherent random-access reads relative to a designated computational "truth-table" basis on the memory register. This work studies restricted-access…

Quantum Physics · Physics 2025-12-23 Leonardo Bohac

In a zero-trust fabless paradigm, designers are increasingly concerned about hardware-based attacks on the semiconductor supply chain. Logic locking is a design-for-trust method that adds extra key-controlled gates in the circuits to…

Cryptography and Security · Computer Science 2024-02-07 Yeganeh Aghamohammadi , Amin Rezaei

String diagrams are a powerful tool for reasoning about physical processes, logic circuits, tensor networks, and many other compositional structures. The distinguishing feature of these diagrams is that edges need not be connected to…

Category Theory · Mathematics 2010-11-19 Lucas Dixon , Aleks Kissinger

In a process algebra with hiding and recursion it is possible to create processes which compute internally without ever communicating with their environment. Such processes are said to diverge or livelock. In this paper we show how it is…

Logic in Computer Science · Computer Science 2015-07-01 Joel Ouaknine , Hristina Palikareva , A. W. Roscoe , James Worrell

The fundamental challenge in causal induction is to infer the underlying graph structure given observational and/or interventional data. Most existing causal induction algorithms operate by generating candidate graphs and evaluating them…

This paper surveys studies on the use of neural networks for optimization in the training-data-free setting. Specifically, we examine the dataless application of neural network architectures in optimization by re-parameterizing problems…

Machine Learning · Computer Science 2025-10-31 Alvaro Velasquez , Susmit Jha , Ismail R. Alkhouri

Reversible computing is a paradigm of computation that reflects physical reversibility, one of the fundamental microscopic laws of Nature. In this survey, we discuss topics on reversible logic elements with memory (RLEM), which can be used…

Formal Languages and Automata Theory · Computer Science 2013-09-06 Kenichi Morita

The $k$-set agreement problem is a generalization of the consensus problem. Namely, assuming each process proposes a value, each non-faulty process has to decide a value such that each decided value was proposed, and no more than $k$…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-03 Zohir Bouzid , Michel Raynal , Pierre Sutra

The rapid advancement of deep neural networks has significantly improved various tasks, such as image and speech recognition. However, as the complexity of these models increases, so does the computational cost and the number of parameters,…

Machine Learning · Computer Science 2023-07-18 Davide Giacomini , Maeesha Binte Hashem , Jeremiah Suarez , Swarup Bhunia , Amit Ranjan Trivedi

Degree-based graph construction is an ubiquitous problem in network modeling, ranging from social sciences to chemical compounds and biochemical reaction networks in the cell. This problem includes existence, enumeration, exhaustive…

Combinatorics · Mathematics 2009-08-27 Hyunju Kim , Zoltan Toroczkai , Péter L. Erdős , István Miklós , László Á. Székely

In lifelong learning systems based on artificial neural networks, one of the biggest obstacles is the inability to retain old knowledge as new information is encountered. This phenomenon is known as catastrophic forgetting. In this paper,…

Machine Learning · Computer Science 2022-08-16 Alexander Ororbia , Ankur Mali , Daniel Kifer , C. Lee Giles

The emergence of a new, open, and free instruction set architecture, RISC-V, has heralded a new era in microprocessor architectures. Starting with low-power, low-performance prototypes, the RISC-V community has a good chance of moving…

Performance · Computer Science 2023-09-06 Valentin Volokitin , Evgeny Kozinov , Valentina Kustikova , Alexey Liniov , Iosif Meyerov