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We describe a generalization of the group testing problem termed symmetric group testing. Unlike in classical binary group testing, the roles played by the input symbols zero and one are "symmetric" while the outputs are drawn from a…

Information Theory · Computer Science 2011-08-16 Amin Emad , Jun Shen , Olgica Milenkovic

We consider the hypothesis testing problem of deciding whether an observed high-dimensional vector has independent normal components or, alternatively, if it has a small subset of correlated components. The correlated components may have a…

Statistics Theory · Mathematics 2012-06-04 Ery Arias-Castro , Sébastien Bubeck , Gábor Lugosi

Identification of up to $d$ defective items and up to $h$ inhibitors in a set of $n$ items is the main task of non-adaptive group testing with inhibitors. To efficiently reduce the cost of this Herculean task, a subset of the $n$ items is…

Information Theory · Computer Science 2019-01-10 Thach V. Bui , Minoru Kuribayashi , Tetsuya Kojima , Isao Echizen

There is an increasing interest in algorithms to learn invariant correlations across training environments. A big share of the current proposals find theoretical support in the causality literature but, how useful are they in practice? The…

Machine Learning · Computer Science 2021-02-23 Benjamin Aubin , Agnieszka Słowik , Martin Arjovsky , Leon Bottou , David Lopez-Paz

The problem of robust binary hypothesis testing is studied. Under both hypotheses, the data-generating distributions are assumed to belong to uncertainty sets constructed through moments; in particular, the sets contain distributions whose…

Statistics Theory · Mathematics 2024-01-09 Akshayaa Magesh , Zhongchang Sun , Venugopal V. Veeravalli , Shaofeng Zou

In this paper, our interest is in the problem of simultaneous hypothesis testing when the test statistics corresponding to the individual hypotheses are possibly correlated. Specifically, we consider the case when the test statistics…

Statistics Theory · Mathematics 2019-01-14 Anupam Kundu , Subir Kumar Bhandari

The two-sender unicast index coding problem consists of finding optimal coded transmissions from the two senders which collectively know the messages demanded by all the receivers. Each receiver demands a unique message. One important class…

Information Theory · Computer Science 2018-08-30 Chinmayananda Arunachala , Vaneet Aggarwal , B. Sundar Rajan

Cascaded binary hypothesis testing is studied in this paper with two decision centers at the relay and the receiver. All terminals have their own observations, where we assume that the observations at the transmitter, the relay, and the…

Information Theory · Computer Science 2021-06-24 Mustapha Hamad , Michèle Wigger , Mireille Sarkiss

This paper characterizes the optimal type-II error exponent for a distributed hypothesis testing-against-independence problem when the \emph{expected} rate of the sensor-detector link is constrained. Unlike for the well-known…

Information Theory · Computer Science 2019-10-21 Sadaf Salehkalaibar , Michele Wigger

We investigate the order of the variance of the optimal alignments score of two independent iid binary random words having the same length. The letters are equiprobable, but the scoring function is such that one letter has a larger score…

Probability · Mathematics 2016-06-17 Christian Houdré , Heinrich Matzinger

We consider the problem of testing whether pairs of univariate random variables are associated. Few tests of independence exist that are consistent against all dependent alternatives and are distribution free. We propose novel tests that…

Methodology · Statistics 2014-12-09 Ruth Heller , Yair Heller , Shachar Kaufman , Malka Gorfine

The distributed linearly separable computation problem finds extensive applications across domains such as distributed gradient coding, distributed linear transform, real-time rendering, etc. In this paper, we investigate this problem in a…

Information Theory · Computer Science 2024-01-30 Haoning Chen , Minquan Cheng , Zhenhao Huang , Youlong Wu

Multi-class classification is mandatory for real world problems and one of promising techniques for multi-class classification is Error Correcting Output Code. We propose a method for constructing the Error Correcting Output Code to obtain…

Machine Learning · Computer Science 2013-12-30 Patoomsiri Songsiri , Thimaporn Phetkaew , Ryutaro Ichise , Boonserm Kijsirikul

The construction of optimal linear block error-correcting codes is not an easy problem, for this, many studies describe methods for generating good error correcting codes in terms of minimum distance. In a previous work, we have presented…

Information Theory · Computer Science 2015-09-11 M. Askali , S. Nouh , A. Azouaoui , M. Belkasmi

This work studies the theoretical rules of feature selection in linear discriminant analysis (LDA), and a new feature selection method is proposed for sparse linear discriminant analysis. An $l_1$ minimization method is used to select the…

Methodology · Statistics 2013-04-23 Cheng Wang , Longbing Cao , Baiqi Miao

This paper provides a statistical method to test whether a system that performs a binary sequential hypothesis test is optimal in the sense of minimizing the average decision times while taking decisions with given reliabilities. The…

Information Theory · Computer Science 2018-01-08 Meik Dörpinghaus , Izaak Neri , Édgar Roldán , Heinrich Meyr , Frank Jülicher

We study the following one-way asymmetric transmission problem, also a variant of model-based compressed sensing: a resource-limited encoder has to report a small set $S$ from a universe of $N$ items to a more powerful decoder (server). The…

Data Structures and Algorithms · Computer Science 2018-07-30 Alexandr Andoni , Javad Ghaderi , Daniel Hsu , Dan Rubenstein , Omri Weinstein

We study the energy performance of random linear network coding for time division duplexing channels. We assume a packet erasure channel with nodes that cannot transmit and receive information simultaneously. The sender transmits coded data…

Information Theory · Computer Science 2009-01-05 Daniel E. Lucani , Milica Stojanovic , Muriel Médard

This paper considers an optimization problem for a dynamical system whose evolution depends on a collection of binary decision variables. We develop scalable approximation algorithms with provable suboptimality bounds to provide…

Optimization and Control · Mathematics 2016-10-31 Insoon Yang , Samuel A. Burden , Ram Rajagopal , S. Shankar Sastry , Claire J. Tomlin

We show that errors in data transmitted through linear codes can be thought of as codewords of minimum weight of new linear codes. To determine errors we can then use methods specific to finding such special codewords. One of these methods…

Commutative Algebra · Mathematics 2015-05-12 Benjamin Anzis , Stefan Tohaneanu
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