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Measurements performed on distant parts of an entangled quantum state can generate correlations incompatible with classical theories respecting the assumption of local causality. This is the phenomenon known as quantum non-locality that,…

Quantum Physics · Physics 2018-02-28 S. G. A. Brito , B. Amaral , R. Chaves

Cross Entropy (CE) has an important role in machine learning and, in particular, in neural networks. It is commonly used in neural networks as the cost between the known distribution of the label and the Softmax/Sigmoid output. In this…

Machine Learning · Computer Science 2020-07-17 Ron Shoham , Haim Permuter

Orbits of graphs under local complementation (LC) and edge local complementation (ELC) have been studied in several different contexts. For instance, there are connections between orbits of graphs and error-correcting codes. We define a new…

Combinatorics · Mathematics 2013-08-09 Lars Eirik Danielsen , Matthew G. Parker , Constanza Riera , Joakim Grahl Knudsen

The outcomes of local measurements made on entangled systems can be certified to be random provided that the generated statistics violate a Bell inequality. This way of producing randomness relies only on a minimal set of assumptions…

Extensive theoretical and experimental investigations on multipartite systems close to an avoided energy-level crossing reveal interesting features such as the extremisation of entanglement. Conventionally, the estimation of entanglement…

Quantum Physics · Physics 2020-12-30 B. Sharmila , S. Lakshmibala , V. Balakrishnan

Multipartite entanglement is an essential resource for quantum communication, quantum computing, quantum sensing, and quantum networks. The utility of a quantum state, $|\psi\rangle$, for these applications is often directly related to the…

Quantum Physics · Physics 2022-01-05 Jacob L. Beckey , N. Gigena , Patrick J. Coles , M. Cerezo

We discuss particle entanglement in systems of indistinguishable bosons and fermions, in finite Hilbert spaces, with focus on operational measures of quantum correlations. We show how to use von Neumann entropy, Negativity and entanglement…

Quantum Physics · Physics 2013-02-22 Fernando Iemini , Reinaldo O. Vianna

How can we characterize different types of correlation between quantum systems? Since correlations cannot be generated locally, we take any real function of a multipartite state which cannot increase under local operations to measure a…

Quantum Physics · Physics 2020-07-27 Joshua Levin , Graeme Smith

Here we discuss a particle-based approach to deal with systems of many identical quantum objects (particles) which never employs labels to mark them. We show that it avoids both methodological problems and drawbacks in the study of quantum…

Quantum Physics · Physics 2018-06-18 Giuseppe Compagno , Alessia Castellini , Rosario Lo Franco

In the context of cluster analysis and graph partitioning, many external evaluation measures have been proposed in the literature to compare two partitions of the same set. This makes the task of selecting the most appropriate measure for a…

Machine Learning · Computer Science 2021-02-09 Nejat Arinik , Vincent Labatut , Rosa Figueiredo

Class imbalance is an intrinsic characteristic of multi-label data. Most of the labels in multi-label data sets are associated with a small number of training examples, much smaller compared to the size of the data set. Class imbalance…

Machine Learning · Computer Science 2018-11-07 Bin Liu , Grigorios Tsoumakas

Signed graphs are equipped with both positive and negative edge weights, encoding pairwise correlations as well as anti-correlations in data. A balanced signed graph has no cycles of odd number of negative edges. Laplacian of a balanced…

Machine Learning · Computer Science 2024-09-13 Haruki Yokota , Hiroshi Higashi , Yuichi Tanaka , Gene Cheung

Identifying low-dimensional latent structures within high-dimensional data has long been a central topic in the machine learning community, driven by the need for data compression, storage, transmission, and deeper data understanding.…

Machine Learning · Statistics 2025-03-28 Ye Tian , Sanyou Wu , Long Feng

Current graph neural networks (GNNs) that tackle node classification on graphs tend to only focus on nodewise scores and are solely evaluated by nodewise metrics. This limits uncertainty estimation on graphs since nodewise marginals do not…

Machine Learning · Computer Science 2022-10-28 Hans Hao-Hsun Hsu , Yuesong Shen , Daniel Cremers

In arXiv:1208.0365 entanglement polytopes where introduced as a coarsening of the SLOCC classification of multipartite entanglement. The advantages of classifying entanglement by entanglement polytopes are a finite hierarchy for all…

Quantum Physics · Physics 2018-08-13 Konstantin Wernli

This article introduces PnCP, a MATLAB toolbox for constructing positive maps which are not completely positive. We survey optimization and sum of squares relaxation techniques to find the most numerically efficient methods for this…

Optimization and Control · Mathematics 2020-01-07 Abhishek Bhardwaj

We derive quantitative relations among several naturally defined measures of classical and nonclassical correlations in a bipartite quantum state. We also obtain an upper bound of entanglement irreversibility and a sufficient condition for…

Quantum Physics · Physics 2012-07-30 Shengjun Wu

We report results of an investigation of relativistic causality constraints on the measurability of nonlocal variables. We show that measurability of certain nondegenerate variables with entangled eigenstates contradicts the principle of…

High Energy Physics - Theory · Physics 2007-05-23 Lev Vaidman

We investigate the complexity cost of demonstrating the key types of nonclassical correlations --- Bell inequality violation, EPR-steering, and entanglement --- with independent agents, theoretically and in a photonic experiment. We show…

Assessing disease severity with ordinal classes, where each class reflects increasing severity levels, benefits from loss functions designed for this ordinal structure. Traditional categorical loss functions, like Cross-Entropy (CE), often…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Gorkem Polat , Ümit Mert Çağlar , Alptekin Temizel
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