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This technical report provides proofs for the claims in the paper "A Full Picture in Conformance Checking: Efficiently Summarizing All Optimal Alignments".

Information Theory · Computer Science 2025-06-13 Philipp Bär , Moe T. Wynn , Sander J. J. Leemans

The network of networks(NON) research is focused on studying the properties of n interdependent networks which is ubiquitous in the real world. Identifying the influential nodes in the network of networks is theoretical and practical…

Social and Information Networks · Computer Science 2015-01-26 Meizhu Li , Qi Zhang , Qi Liu , Yong Deng

We first present a determinant inequality related to partial traces for positive semidefinite block matrices. Our result extends a result of Lin [Czech. Math. J. 66 (2016)] and improves a result of Kuai [Linear Multilinear Algebra 66…

Functional Analysis · Mathematics 2022-01-20 Yongtao Li

This paper deals with the design of Excitation and Measurement Patterns (EMPs) for the identification of dynamical networks, when the objective is to identify only a subnetwork embedded in a larger network. Recent results have shown how to…

Systems and Control · Electrical Eng. & Systems 2024-02-23 Eduardo Mapurunga , Michel Gevers , Alexandre S. Bazanella

In this paper, we prove the existence of fundamental relations between information theory and estimation theory for network-coded flows. When the network is represented by a directed graph G=(V, E) and under the assumption of uncorrelated…

Information Theory · Computer Science 2016-11-17 Samah A. M. Ghanem

In this work, some counterexamples are given to refute some results reported in the paper by Guo and Li [8] (J Optim Theory Appl 162,(2014), 821-844). We correct the faulty in some of their theorems and we present alternative proofs.…

Functional Analysis · Mathematics 2019-02-12 Allahkaram Shafie , Fari Bozorgnia

Quantum nonlocality can be demonstrated without inputs (i.e. each party using a fixed measurement setting) in a network with independent sources. Here we consider this effect on ring networks, and show that the underlying quantum strategy…

Quantum Physics · Physics 2025-02-11 Pavel Sekatski , Sadra Boreiri , Nicolas Brunner

This paper extends previous work with network fragments and situation-specific network construction. We formally define the asymmetry network, an alternative representation for a conditional probability table. We also present an…

Artificial Intelligence · Computer Science 2013-01-30 Suzanne M. Mahoney , Kathryn Blackmond Laskey

In the paper are proved theorems, which amplify the results of my paper "On the difference equation of Poincare type (Part 3)", Max-Plank-Institut fuer Mathematik, Bonn, Preprint Series, 2004, 09, 1-34.

Number Theory · Mathematics 2007-05-23 L. A. Gutnik

Tensor networks provide extremely powerful tools for the study of complex classical and quantum many-body problems. Over the last two decades, the increment in the number of techniques and applications has been relentless, and especially…

Quantum Physics · Physics 2023-03-29 Mari Carmen Bañuls

This paper introduces a novel problem, distributional information embedding, motivated by the practical demands of multi-bit watermarking for large language models (LLMs). Unlike traditional information embedding, which embeds information…

Cryptography and Security · Computer Science 2025-07-03 Haiyun He , Yepeng Liu , Ziqiao Wang , Yongyi Mao , Yuheng Bu

Identifiability of a single module in a network of transfer functions is determined by whether a particular transfer function in the network can be uniquely distinguished within a network model set, on the basis of data. Whereas previous…

Systems and Control · Electrical Eng. & Systems 2021-12-22 Shengling Shi , Xiaodong Cheng , Paul M. J. Van den Hof

When neural networks are employed for high-stakes decision-making, it is desirable that they provide explanations for their prediction in order for us to understand the features that have contributed to the decision. At the same time, it is…

Machine Learning · Computer Science 2022-05-10 Penny Chong , Ngai-Man Cheung , Yuval Elovici , Alexander Binder

In this note, we prove a conjecture proposed by Tao Zhang, Shuxing Li, Tao Feng and Gennian Ge, IEEE Transaction on Information Theory, vol. 60, no. 5, May 2014. This conjecture is about the cross correlation distribution of ternary…

Information Theory · Computer Science 2014-09-04 Hai Xiong , Longjiang Qu

With the widespread use of information technologies, information networks are becoming increasingly popular to capture complex relationships across various disciplines, such as social networks, citation networks, telecommunication networks,…

Social and Information Networks · Computer Science 2018-07-20 Daokun Zhang , Jie Yin , Xingquan Zhu , Chengqi Zhang

We derive a general framework that connects every positive map with a corresponding witness for partial separability in multipartite quantum systems. We show that many previous approaches were intimately connected to the witnesses derived…

Quantum Physics · Physics 2014-09-10 Marcus Huber , Ritabrata Sengupta

As machine learning technology gets applied to actual products and solutions, new challenges have emerged. Models unexpectedly fail to generalize to small changes in the distribution, tend to be confident on novel data they have never seen,…

Machine Learning · Computer Science 2023-10-13 Bálint Mucsányi , Michael Kirchhof , Elisa Nguyen , Alexander Rubinstein , Seong Joon Oh

Our objective in this note is to comment briefly on the newly emerging literature on computer-aided proofs in Social Choice Theory. We shall specifically comment on two papers, one by Tang and Lin (2009) and another by Geist and Endriss…

Logic in Computer Science · Computer Science 2014-03-17 Siddharth Chatterjee , Arunava Sen

Quantum entanglement is the core resource in quantum information processing and quantum computing. It is an significant challenge to effectively characterize the entanglement of quantum states. Recently, elegant separability criterion is…

Quantum Physics · Physics 2023-02-22 Tinggui Zhang , Naihuan Jing , Shao-Ming Fei

We propose a novel method for network inference from partially observed edges using a node-specific degree prior. The degree prior is derived from observed edges in the network to be inferred, and its hyper-parameters are determined by…

Machine Learning · Statistics 2016-02-09 Qingming Tang , Lifu Tu , Weiran Wang , Jinbo Xu
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