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We address the problem of unambiguous comparison of a pair of unknown qudit unitary channels. Using the framework of process positive operator valued measures (PPOVM) we characterize all solutions and identify the optimal ones. We prove…

Quantum Physics · Physics 2009-01-09 Michal Sedlak , Mario Ziman

Program equivalence in linear contexts, where programs are used or executed exactly once, is an important issue in programming languages. However, existing techniques like those based on bisimulations and logical relations only target at…

Programming Languages · Computer Science 2011-10-12 Yuxin Deng , Yu Zhang

The pairwise comparisons method is a convenient tool used when the relative order among different concepts (alternatives) needs to be determined. One popular implementation of the method is based on solving an eigenvalue problem for the…

Discrete Mathematics · Computer Science 2015-09-25 Konrad Kułakowski

Similarity functions measure how comparable pairs of elements are, and play a key role in a wide variety of applications, e.g., notions of Individual Fairness abiding by the seminal paradigm of Dwork et al., as well as Clustering problems.…

Machine Learning · Computer Science 2023-10-24 Leonidas Tsepenekas , Ivan Brugere , Freddy Lecue , Daniele Magazzeni

We compare mechanisms for compensation handling and dynamic update in calculi for concurrency. These mechanisms are increasingly relevant in the specification of reliable communicating systems. Compensations and updates are intuitively…

Logic in Computer Science · Computer Science 2015-08-28 Jovana Dedeić , Jovanka Pantović , Jorge A. Pérez

Employing a recently proposed separability criterion we develop analytical lower bounds for the concurrence and for the entanglement of formation of bipartite quantum systems. The separability criterion is based on a nondecomposable…

Quantum Physics · Physics 2007-05-23 Heinz-Peter Breuer

Development of energy and performance-efficient embedded software is increasingly relying on application of complex transformations on the critical parts of the source code. Designers applying such nontrivial source code transformations are…

Logic in Computer Science · Computer Science 2011-11-09 K. C. Shashidhar , Maurice Bruynooghe , Francky Catthoor , Gerda Janssens

We encode arrays as functions which, in turn, are encoded as sets of ordered pairs. The set cardinality of each of these functions coincides with the length of the array it is representing. Then we define a fragment of set theory that is…

Logic in Computer Science · Computer Science 2026-05-12 Maximiliano Cristiá , Gianfranco Rossi

Modern predictive analytics underpinned by machine learning techniques has become a key enabler to the automation of data-driven decision making. In the context of business process management, predictive analytics has been applied to making…

Machine Learning · Computer Science 2020-06-09 Renuka Sindhgatta , Chun Ouyang , Catarina Moreira

How can one recognize coordination languages and technologies? As this report shows, the common approach that contrasts coordination with computation is intellectually unsound: depending on the selected understanding of the word…

Programming Languages · Computer Science 2013-07-19 Raphael 'kena' Poss

Verifying whether a procedure is observationally pure is useful in many software engineering scenarios. An observationally pure procedure always returns the same value for the same argument, and thus mimics a mathematical function. The…

Software Engineering · Computer Science 2019-02-15 Himanshu Arora , Raghavan Komondoor , G. Ramalingam

We propose a new perspective for the evaluation of matching procedures by considering the complexity of the function class they belong to. Under this perspective we provide theoretical guarantees on post-matching covariate balance through a…

Statistics Theory · Mathematics 2023-01-04 Efrén Cruz Cortés , Kevin Josey , Fan Yang , Debashis Ghosh

This review aims to draw attention to two issues of concern when we set out to make machine learning work in the chemical and materials domain, i.e., statistical loss function metrics for the validation and benchmarking of data-derived…

Chemical Physics · Physics 2021-01-26 Gaurav Vishwakarma , Aditya Sonpal , Johannes Hachmann

Principles of analogical reasoning have recently been applied in the context of machine learning, for example to develop new methods for classification and preference learning. In this paper, we argue that, while analogical reasoning is…

Machine Learning · Computer Science 2020-05-27 Eyke Hüllermeier

Understanding program code is a complicated endeavor. As such, myriad different factors can influence the outcome. Investigations of program comprehension, and in particular those using controlled experiments, have to take these factors…

Software Engineering · Computer Science 2021-03-17 Dror G. Feitelson

Contextuality provides a unifying paradigm for nonclassical aspects of quantum probabilities and resources of quantum information. Unfortunately, most forms of quantum contextuality remain experimentally unexplored due to the difficulty of…

Quantum Physics · Physics 2016-03-02 Adán Cabello

Proposed is a new formal approach for solution of extreme multi-criteria problems transforming them into single-criterion mathematical models, without any additional information. Transforming rules are based on comparison standards and…

Optimization and Control · Mathematics 2007-05-23 V. O. Groppen

Eliciting relevance judgments for ranking evaluation is labor-intensive and costly, motivating careful selection of which documents to judge. Unlike traditional approaches that make this selection deterministically, probabilistic sampling…

Information Retrieval · Computer Science 2016-04-26 Tobias Schnabel , Adith Swaminathan , Peter Frazier , Thorsten Joachims

For systems consisting of distinguishable particles, there exists an agreed upon notion of entanglement which is fundamentally based on the possibility of addressing individually each one of the constituent parties. Instead, the…

Quantum Physics · Physics 2020-09-24 F. Benatti , R. Floreanini , F. Franchini , U. Marzolino

Linear classifier probes are frequently utilized to better understand how neural networks function. Researchers have approached the problem of determining unit importance in neural networks by probing their learned, internal…

Machine Learning · Computer Science 2022-11-09 Lucas Hayne , Abhijit Suresh , Hunar Jain , Rahul Kumar , R. McKell Carter