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Nowadays there are several classes of constrained codes intended for different applications. The following two large classes can be distinguished. The first class contains codes with local constraints; for example, the source data must be…

Information Theory · Computer Science 2024-05-27 Boris Ryabko

Most existing set encoding algorithms operate under the implicit assumption that all the set elements are accessible, and that there are ample computational and memory resources to load the set into memory during training and inference.…

Machine Learning · Computer Science 2021-10-27 Bruno Andreis , Jeffrey Willette , Juho Lee , Sung Ju Hwang

We consider theoretical limits of partial secrecy in a setting where an eavesdropper attempts to causally reconstruct an information sequence with low distortion based on an intercepted transmission and the past of the sequence. The…

Information Theory · Computer Science 2010-08-05 Paul Cuff

Monotone systems, also known as order-preserving or cooperative systems, are prevalent in models of engineering applications such as transportation and biological networks. In this paper, we investigate the problem of finding a control…

Systems and Control · Computer Science 2018-07-30 Sadra Sadraddini , Calin Belta

We introduce a new family of codes, termed weighted superimposed codes (WSCs). This family generalizes the class of Euclidean superimposed codes (ESCs), used in multiuser identification systems. WSCs allow for discriminating all bounded,…

Information Theory · Computer Science 2008-12-18 Wei Dai , Olgica Milenkovic

Can pretrained models generalize to new datasets without any retraining? We deploy pretrained image models on datasets they were not trained for, and investigate whether their embeddings form meaningful clusters. Our suite of benchmarking…

Machine Learning · Computer Science 2024-06-05 Scott C. Lowe , Joakim Bruslund Haurum , Sageev Oore , Thomas B. Moeslund , Graham W. Taylor

This article introduces a novel communication scheme, termed coded compressed sensing, for unsourced multiple-access communication. The proposed divide-and-conquer approach leverages recent advances in compressed sensing and forward error…

Signal Processing · Electrical Eng. & Systems 2019-06-26 Vamsi K. Amalladinne , Jean-Francois Chamberland , Krishna R. Narayanan

Programs to solve so-called constraint problems are complex pieces of software which require many design decisions to be made more or less arbitrarily by the implementer. These decisions affect the performance of the finished solver…

Artificial Intelligence · Computer Science 2010-05-20 Lars Kotthoff , Ian Gent , Ian Miguel

Constrained codes are used to eliminate error-prone patterns in various practical systems. Recently, we introduced efficient binary symmetric lexicographically-ordered constrained (LOCO) codes and asymmetric LOCO (A-LOCO) codes to increase…

Information Theory · Computer Science 2020-10-20 Jessica Centers , Xinyu Tan , Ahmed Hareedy , Robert Calderbank

The completely bounded trace and spectral norms in finite dimensions are shown to be expressible by semidefinite programs. This provides an efficient method by which these norms may be both calculated and verified, and gives alternate…

Quantum Physics · Physics 2009-04-15 John Watrous

We introduce the concept of generalized concatenated quantum codes. This generalized concatenation method provides a systematical way for constructing good quantum codes, both stabilizer codes and nonadditive codes. Using this method, we…

Quantum Physics · Physics 2009-05-24 Markus Grassl , Peter Shor , Graeme Smith , John Smolin , Bei Zeng

Not long ago, it was thought that only software applications and general purpose digital systems i.e. computers were prone to various types of attacks against their security. The underlying hardware, hardware implementations of these…

Cryptography and Security · Computer Science 2016-10-04 Muhammad Farooq-i-Azam , Muhammad Naeem Ayyaz

Covert communication is the undetected transmission of sensitive information over a communication channel. In wireless communication systems, channel impairments such as signal fading present challenges in the effective implementation and…

Information Theory · Computer Science 2025-09-29 Amir Reza Ramtin , Dennis Goeckel , Don Towsley

Spatial constraint systems (scs) are semantic structures for reasoning about spatial and epistemic information in concurrent systems. They have been used to reason about beliefs, lies, and group epistemic behaviour inspired by social…

Multiagent Systems · Computer Science 2019-08-26 Frank Valencia

Semidefinite programming is an important tool to tackle several problems in data science and signal processing, including clustering and community detection. However, semidefinite programs are often slow in practice, so speed up techniques…

Optimization and Control · Mathematics 2022-05-11 Pedro Abdalla , Afonso S. Bandeira

Constrained clustering allows the training of classification models using pairwise constraints only, which are weak and relatively easy to mine, while still yielding full-supervision-level model performance. While they perform well even in…

Machine Learning · Computer Science 2023-11-28 Jann Goschenhofer , Bernd Bischl , Zsolt Kira

The demand of two-dimensional source coding and constrained coding has been getting higher these days, but compared to the one-dimensional case, many problems have remained open as the analysis is cumbersome. A main reason for that would be…

Information Theory · Computer Science 2016-02-03 Takahiro Ota , Akiko Manada , Hiroyoshi Morita

An `obfuscation' for encrypted computing is quantified exactly here, leading to an argument that security against polynomial-time attacks has been achieved for user data via the deliberately `chaotic' compilation required for security…

Cryptography and Security · Computer Science 2019-04-30 Peter T. Breuer

In data storage and data transmission, certain patterns are more likely to be subject to error when written (transmitted) onto the media. In magnetic recording systems with binary data and bipolar non-return-to-zero signaling, patterns that…

Information Theory · Computer Science 2020-02-25 Ahmed Hareedy , Robert Calderbank

Semi-supervised learning is an important and active topic of research in pattern recognition. For classification using linear discriminant analysis specifically, several semi-supervised variants have been proposed. Using any one of these…

Machine Learning · Statistics 2014-11-18 Jesse H. Krijthe , Marco Loog
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