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We discuss replica analytic continuation using several simple models in order to prove mathematically the validity of replica analysis, which is used in a wide range of fields related to large scale complex systems. While replica analysis…

Disordered Systems and Neural Networks · Physics 2016-06-24 Takashi Shinzato

This paper provides foundations for strong (that is, possibly under abstraction) call-by-value evaluation for the lambda-calculus. Recently, Accattoli et al. proposed a form of call-by-value strong evaluation for the lambda-calculus, the…

Logic in Computer Science · Computer Science 2023-09-22 Beniamino Accattoli , Giulio Guerrieri , Maico Leberle

We introduce two extensions of the $\lambda$-calculus with a probabilistic choice operator, $\Lambda_\oplus^{cbv}$ and $\Lambda_\oplus^{cbn}$, modeling respectively call-by-value and call-by-name probabilistic computation. We prove that…

Logic in Computer Science · Computer Science 2019-05-13 Claudia Faggian , Simona Ronchi della Rocca

Can we effectively learn a nonlinear representation in time comparable to linear learning? We describe a new algorithm that explicitly and adaptively expands higher-order interaction features over base linear representations. The algorithm…

Machine Learning · Computer Science 2014-10-03 Alekh Agarwal , Alina Beygelzimer , Daniel Hsu , John Langford , Matus Telgarsky

Two-sample hypothesis testing for network comparison presents many significant challenges, including: leveraging repeated network observations and known node registration, but without requiring them to operate; relaxing strong structural…

Methodology · Statistics 2024-02-05 Meijia Shao , Dong Xia , Yuan Zhang , Qiong Wu , Shuo Chen

A standard informal method for analyzing the asymptotic complexity of a program is to extract a recurrence that describes its cost in terms of the size of its input, and then to compute a closed-form upper bound on that recurrence. We give…

Programming Languages · Computer Science 2022-08-09 Norman Danner , Daniel R. Licata

The task of determining labels of all network nodes based on the knowledge about network structure and labels of some training subset of nodes is called the within-network classification. It may happen that none of the labels of the nodes…

Machine Learning · Statistics 2015-10-06 Tomasz Kajdanowicz , Radosław Michalski , Katarzyna Musiał , Przemysław Kazienko

We establish a general framework for reasoning about the relationship between call-by-value and call-by-name. In languages with computational effects, call-by-value and call-by-name executions of programs often have different, but related,…

Programming Languages · Computer Science 2024-08-07 Dylan McDermott , Alan Mycroft

In many fields of experimental science, papers that failed to replicate continue to be cited as a result of the poor discoverability of replication studies. As a first step to creating a system that automatically finds replication studies…

Digital Libraries · Computer Science 2023-11-28 Bob de Ruiter

Named entity recognition often fails in idiosyncratic domains. That causes a problem for depending tasks, such as entity linking and relation extraction. We propose a generic and robust approach for high-recall named entity recognition. Our…

Computation and Language · Computer Science 2016-08-25 Sebastian Arnold , Felix A. Gers , Torsten Kilias , Alexander Löser

Learning relations based on evidence from knowledge bases relies on processing the available relation instances. Many relations, however, have clear domain and range, which we hypothesize could help learn a better, more generalizing, model.…

Artificial Intelligence · Computer Science 2018-03-05 Bhushan Kotnis , Vivi Nastase

A typical way of analyzing the time complexity of functional programs is to extract a recurrence expressing the running time of the program in terms of the size of its input, and then to solve the recurrence to obtain a big-O bound. For…

Programming Languages · Computer Science 2020-08-03 Joseph W. Cutler , Daniel R. Licata , Norman Danner

In rule-based systems, goal-oriented computations correspond naturally to the possible ways that an observation may be explained. In some applications, we need to compute explanations for a series of observations with the same domain. The…

Artificial Intelligence · Computer Science 2007-05-23 Fangzhen Lin , Jia-Huai You

Replicability is a fundamental challenge in reinforcement learning (RL), as RL algorithms are empirically observed to be unstable and sensitive to variations in training conditions. To formally address this issue, we study \emph{list…

Machine Learning · Computer Science 2025-12-02 Bohan Zhang , Michael Chen , A. Pavan , N. V. Vinodchandran , Lin F. Yang , Ruosong Wang

Empirical science needs to be based on facts and claims that can be reproduced. This calls for replicating the studies that proclaim the claims, but practice in most fields still fails to implement this idea. When such studies emerged in…

Other Statistics · Statistics 2025-08-27 Werner A. Stahel

Top-down and bottom-up theorem proving approaches each have specific advantages and disadvantages. Bottom-up provers profit from strong redundancy control but suffer from the lack of goal-orientation, whereas top-down provers are…

Artificial Intelligence · Computer Science 2011-05-30 M. Fuchs , D. Fuchs

Substructural type systems, such as affine (and linear) type systems, are type systems which impose restrictions on copying (and discarding) of variables, and they have found many applications in computer science, including quantum…

Logic in Computer Science · Computer Science 2021-01-27 Vladimir Zamdzhiev

We introduce proof terms for string rewrite systems and, using these, show that various notions of equivalence on reductions known from the literature can be viewed as different perspectives on the notion of causal equivalence. In…

Logic in Computer Science · Computer Science 2023-03-29 Vincent van Oostrom

Plan Recognition algorithms require to recognize a complete hierarchy explaining the agent's actions and goals. While the output of such algorithms is informative to the recognizer, the cost of its calculation is high in run-time, space,…

Artificial Intelligence · Computer Science 2017-03-03 Retuh Mirsky , Ya'akov , Gal

In this work we study randomised reduction strategies,a notion already known in the context of abstract reduction systems, for the $\lambda$-calculus. We develop a simple framework that allows us to prove a randomised strategy to be…

Logic in Computer Science · Computer Science 2019-11-12 Ugo Dal Lago , Gabriele Vanoni
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