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This paper introduces a new machine architecture for evaluating lambda expressions using the normal-order reduction, which guarantees that every lambda expression will be evaluated if the expression has its normal form and the system has…

Logic in Computer Science · Computer Science 2010-11-05 Anton Salikhmetov

Memory-augmented neural networks consisting of a neural controller and an external memory have shown potentials in long-term sequential learning. Current RAM-like memory models maintain memory accessing every timesteps, thus they do not…

Machine Learning · Computer Science 2019-03-21 Hung Le , Truyen Tran , Svetha Venkatesh

We introduce a general scheme for sequential one-way quantum computation where static systems with long-living quantum coherence (memories) interact with moving systems that may possess very short coherence times. Both the generation of the…

Quantum Physics · Physics 2015-05-27 Augusto J. Roncaglia , Leandro Aolita , Alessandro Ferraro , Antonio Acin

The classical lambda calculus may be regarded both as a programming language and as a formal algebraic system for reasoning about computation. It provides a computational model equivalent to the Turing machine, and continues to be of…

Quantum Physics · Physics 2007-05-23 Andre van Tonder

There are a few different ways to extend regular nonlinear dynamical systems by introducing power-law memory or considering fractional differential/difference equations instead of integer ones. This extension allows the introduction of…

Chaotic Dynamics · Physics 2017-09-04 Mark Edelman

This paper proposes new mathematical models of the untyped Lambda-mu calculus. One is called the stream model, which is an extension of the lambda model, in which each term is interpreted as a function from streams to individual data. The…

Logic in Computer Science · Computer Science 2012-10-12 Koji Nakazawa , Shin-ya Katsumata

We introduce the notion of universal memcomputing machines (UMMs): a class of brain-inspired general-purpose computing machines based on systems with memory, whereby processing and storing of information occur on the same physical location.…

Neural and Evolutionary Computing · Computer Science 2015-12-17 Fabio L. Traversa , Massimiliano Di Ventra

The lambda calculus is a widely accepted computational model of higher-order functional pro- grams, yet there is not any direct and universally accepted cost model for it. As a consequence, the computational difficulty of reducing lambda…

Logic in Computer Science · Computer Science 2012-02-09 Beniamino Accattoli , Ugo Dal Lago

We describe a type system for the linear-algebraic lambda-calculus. The type system accounts for the part of the language emulating linear operators and vectors, i.e. it is able to statically describe the linear combinations of terms…

Logic in Computer Science · Computer Science 2012-08-01 Pablo Arrighi , Alejandro Díaz-Caro , Benoît Valiron

Universal memcomputing machines (UMMs) [IEEE Trans. Neural Netw. Learn. Syst. 26, 2702 (2015)] represent a novel computational model in which memory (time non-locality) accomplishes both tasks of storing and processing of information. UMMs…

Neural and Evolutionary Computing · Computer Science 2019-05-29 Yan Ru Pei , Fabio L. Traversa , Massimiliano Di Ventra

Memory emerges as the core module in the large language model (LLM)-based agents for long-horizon complex tasks (e.g., multi-turn dialogue, game playing, scientific discovery), where memory can enable knowledge accumulation, iterative…

Computation and Language · Computer Science 2026-05-04 Yanchen Wu , Tenghui Lin , Yingli Zhou , Fangyuan Zhang , Qintian Guo , Xun Zhou , Sibo Wang , Xilin Liu , Yuchi Ma , Yixiang Fang

We describe a type system for the linear-algebraic $\lambda$-calculus. The type system accounts for the linear-algebraic aspects of this extension of $\lambda$-calculus: it is able to statically describe the linear combinations of terms…

Logic in Computer Science · Computer Science 2017-05-12 Pablo Arrighi , Alejandro Díaz-Caro , Benoît Valiron

In this paper, we present an extension of $\lambda\mu$-calculus called $\lambda\mu^{++}$-calculus which has the following properties: subject reduction, strong normalization, unicity of the representation of data and thus confluence only on…

Logic · Mathematics 2009-05-05 Karim Nour

Race logic, an arrival-time-coded logic family, has demonstrated energy and performance improvements for applications ranging from dynamic programming to machine learning. However, the ad hoc mappings of algorithms into hardware result in…

Emerging Technologies · Computer Science 2021-05-12 Advait Madhavan , Matthew Daniels , Mark Stiles

Embedding learning, a.k.a. representation learning, has been shown to be able to model large-scale semantic knowledge graphs. A key concept is a mapping of the knowledge graph to a tensor representation whose entries are predicted by models…

Artificial Intelligence · Computer Science 2016-05-10 Volker Tresp , Cristóbal Esteban , Yinchong Yang , Stephan Baier , Denis Krompaß

In this paper we address the question of how to render sequence-level networks better at handling structured input. We propose a machine reading simulator which processes text incrementally from left to right and performs shallow reasoning…

Computation and Language · Computer Science 2016-09-22 Jianpeng Cheng , Li Dong , Mirella Lapata

The $\lambda$-calculus is a handy formalism to specify the evaluation of higher-order programs. It is not very handy, however, when one interprets the specification as an execution mechanism, because terms can grow exponentially with the…

Logic in Computer Science · Computer Science 2019-07-16 Andrea Condoluci , Beniamino Accattoli , Claudio Sacerdoti Coen

System I is a simply-typed lambda calculus with pairs, extended with an equational theory obtained from considering the type isomorphisms as equalities. In this work we propose an extension of System I to polymorphic types, adding the…

Logic in Computer Science · Computer Science 2021-07-28 Cristian F. Sottile , Alejandro Díaz-Caro , Pablo E. Martínez López

We present a study on the integration of Large Language Models (LLMs) in tabular data classification, emphasizing an efficient framework. Building upon existing work done in TabLLM (arXiv:2210.10723), we introduce three novel serialization…

Machine Learning · Computer Science 2023-12-22 Sukriti Jaitly , Tanay Shah , Ashish Shugani , Razik Singh Grewal

In this paper we consider the problem of uniformity testing with limited memory. We observe a sequence of independent identically distributed random variables drawn from a distribution $p$ over $[n]$, which is either uniform or is…

Information Theory · Computer Science 2022-06-22 Tomer Berg , Or Ordentlich , Ofer Shayevitz
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