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Factorization machines (FMs) are a supervised learning approach that can use second-order feature combinations even when the data is very high-dimensional. Unfortunately, despite increasing interest in FMs, there exists to date no efficient…

Machine Learning · Statistics 2016-10-17 Mathieu Blondel , Akinori Fujino , Naonori Ueda , Masakazu Ishihata

Quite often, verification tasks for distributed systems are accomplished via counter abstractions. Such abstractions can sometimes be justified via simulations and bisimulations. In this work, we supply logical foundations to this practice,…

Logic in Computer Science · Computer Science 2017-12-06 Silvio Ghilardi , Elena Pagani

In this paper we introduce a novel family of decision lists consisting of highly interpretable models which can be learned efficiently in a greedy manner. The defining property is that all rules are oriented in the same direction.…

Machine Learning · Statistics 2016-01-12 Marc Goessling , Shan Kang

This paper introduces a new behavioral system model with distinct external and internal signals possibly evolving on different time scales. This allows to capture abstraction processes or signal aggregation in the context of control and…

Systems and Control · Computer Science 2014-02-17 Anne-Kathrin Schmuck , Jörg Raisch

Among the various forms of reasoning studied in the context of artificial intelligence, qualitative reasoning makes it possible to infer new knowledge in the context of imprecise, incomplete information without numerical values. In this…

Artificial Intelligence · Computer Science 2026-02-10 Quentin Cohen-Solal , Alexandre Niveau , Maroua Bouzid

The explorations of models beyond the Standard Model (BSM) naturally involve scans over the unknown BSM parameters. On the other hand, high precision predictions require calculations at the loop-level and thus a renormalization of (some of)…

High Energy Physics - Phenomenology · Physics 2024-07-01 S. Heinemeyer , F. von der Pahlen

We show how the separability problem is dual to that of decomposing any given matrix into a conic combination of rank-one partial isometries, thus offering a duality approach different to the positive maps characterization problem. Several…

Quantum Physics · Physics 2007-05-23 D. Salgado , J. L. Sanchez-Gomez , M. Ferrero

Classification of datasets into two or more distinct classes is an important machine learning task. Many methods are able to classify binary classification tasks with a very high accuracy on test data, but cannot provide any easily…

Machine Learning · Computer Science 2020-08-26 Yashesh Dhebar , Sparsh Gupta , Kalyanmoy Deb

When transforming pairs of independent quantum operations according to the fundamental rules of quantum theory, an intriguing phenomenon emerges: some such higher-order operations may act on the input operations in an indefinite causal…

Quantum Physics · Physics 2022-02-08 Jessica Bavaresco , Mateus Araújo , Časlav Brukner , Marco Túlio Quintino

We show that time complexity analysis of higher-order functional programs can be effectively reduced to an arguably simpler (although computationally equivalent) verification problem, namely checking first-order inequalities for validity.…

Logic in Computer Science · Computer Science 2012-10-26 Ugo Dal Lago , Barbara Petit

A (fragment of a) process algebra satisfies unique parallel decomposition if the definable behaviours admit a unique decomposition into indecomposable parallel components. In this paper we prove that finite processes of the pi-calculus,…

Logic in Computer Science · Computer Science 2016-08-11 Matias David Lee , Bas Luttik

The model of asynchronous programming arises in many contexts, from low-level systems software to high-level web programming. We take a language-theoretic perspective and show general decidability and undecidability results for asynchronous…

Formal Languages and Automata Theory · Computer Science 2023-06-22 Rupak Majumdar , Ramanathan S. Thinniyam , Georg Zetzsche

We define a notion of normal form bisimilarity for the untyped call-by-value lambda calculus extended with the delimited-control operators shift and reset. Normal form bisimilarities are simple, easy-to-use behavioral equivalences which…

Programming Languages · Computer Science 2012-02-29 Dariusz Biernacki , Serguei Lenglet

Input binarization has shown to be an effective way for network acceleration. However, previous binarization scheme could be regarded as simple pixel-wise thresholding operations (i.e., order-one approximation) and suffers a big accuracy…

Computer Vision and Pattern Recognition · Computer Science 2017-08-30 Zefan Li , Bingbing Ni , Wenjun Zhang , Xiaokang Yang , Wen Gao

Accurate calibration of probabilistic predictive models learned is critical for many practical prediction and decision-making tasks. There are two main categories of methods for building calibrated classifiers. One approach is to develop…

Machine Learning · Statistics 2014-01-16 Mahdi Pakdaman Naeini , Gregory F. Cooper , Milos Hauskrecht

We define an equivalence relation on propositions and a proof system where equivalent propositions have the same proofs. The system obtained this way resembles several known non-deterministic and algebraic lambda-calculi.

Logic in Computer Science · Computer Science 2013-04-01 Alejandro Díaz-Caro , Gilles Dowek

We consider anti-unification for simply typed lambda terms in associative, commutative, and associative-commutative theories and develop a sound and complete algorithm which takes two lambda terms and computes their generalizations in the…

Logic in Computer Science · Computer Science 2022-08-02 David M. Cerna , Temur Kutsia

There exists a rich literature of rule formats guaranteeing different algebraic properties for formalisms with a Structural Operational Semantics. Moreover, there exist a few approaches for automatically deriving axiomatizations…

Logic in Computer Science · Computer Science 2013-07-30 Daniel Gebler , Eugen-Ioan Goriac , Mohammad Reza Mousavi

Linearizability has become the key correctness criterion for concurrent data structures, ensuring that histories of the concurrent object under consideration are consistent, where consistency is judged with respect to a sequential history…

Logic in Computer Science · Computer Science 2015-02-03 Brijesh Dongol , John Derrick

Binary classification is one of the most common problem in machine learning. It consists in predicting whether a given element belongs to a particular class. In this paper, a new algorithm for binary classification is proposed using a…

Machine Learning · Computer Science 2019-03-12 Alexandre Quemy
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