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Principal Components Regression (PCR) is a traditional tool for dimension reduction in linear regression that has been both criticized and defended. One concern about PCR is that obtaining the leading principal components tends to be…

Statistics Theory · Mathematics 2017-10-10 Martin Slawski

Sparse random linear network coding (SRLNC) used as a class of erasure codes to ensure the reliability of multicast communications has been widely investigated. However, an exact expression for the decoding success probability of SRLNC is…

Information Theory · Computer Science 2021-08-27 WenLin Chen , Fang Lu , Yan Dong

We analyze the convergence rates of two popular variants of coordinate descent (CD): random CD (RCD), in which the coordinates are sampled uniformly at random, and random-permutation CD (RPCD), in which random permutations are used to…

Optimization and Control · Mathematics 2025-05-30 Donghwa Kim , Jaewook Lee , Chulhee Yun

The bit-error threshold of the standard ensemble of Low Density Parity Check (LDPC) codes is known to be close to capacity, if there is a non-zero fraction of degree-two bit nodes. However, the degree-two bit nodes preclude the possibility…

Information Theory · Computer Science 2013-05-22 Asit Kumar Pradhan , Arunkumar Subramanian , Andrew Thangaraj

The likelihood encoder with a random codebook is demonstrated as an effective tool for source coding. Coupled with a soft covering lemma (associated with channel resolvability), likelihood encoders yield simple achievability proofs for…

Information Theory · Computer Science 2013-08-01 Paul Cuff , Eva C. Song

Most low-density parity-check (LDPC) code constructions are considered over finite fields. In this work, we focus on regular LDPC codes over integer residue rings and analyze their performance with respect to the Lee metric. Their…

Information Theory · Computer Science 2024-08-01 Jessica Bariffi , Hannes Bartz , Gianluigi Liva , Joachim Rosenthal

We present a new model for LT codes which simplifies the analysis of the error probability of decoding by belief propagation. For any given degree distribution, we provide the first rigorous expression for the limiting error probability as…

Information Theory · Computer Science 2007-07-13 Elitza N. Maneva , Amin Shokrollahi

We study ensembles of codes on graphs (generalized low-density parity-check, or LDPC codes) constructed from random graphs and fixed local constrained codes, and their extension to codes on hypergraphs. It is known that the average minimum…

Information Theory · Computer Science 2011-02-22 Alexander Barg , Arya Mazumdar

Error probabilities of random codes for memoryless channels are considered in this paper. In the area of communication systems, admissible error probability is very small and it is sometimes more important to discuss the relative gap…

Information Theory · Computer Science 2015-06-11 Junya Honda

We derive upper and lower bounds for the error exponents of lossless streaming compression of two correlated sources under the blockwise and symbolwise settings. We consider the linear scaling regime in which the delay is a scalar multiple…

Information Theory · Computer Science 2016-02-24 Lin Zhou , Vincent Yan Fu Tan , Mehul Motani

Neural networks can efficiently encode the probability distribution of errors in an error correcting code. Moreover, these distributions can be conditioned on the syndromes of the corresponding errors. This paves a path forward for a…

Quantum Physics · Physics 2017-09-12 Stefan Krastanov , Liang Jiang

Large random matrices appear in different fields of mathematics and physics such as combinatorics, probability theory, statistics, operator theory, number theory, quantum field theory, string theory etc... In the last ten years, they…

Probability · Mathematics 2007-05-23 Alice Guionnet

We analyze the prediction error of principal component regression (PCR) and prove high probability bounds for the corresponding squared risk conditional on the design. Our first main result shows that PCR performs comparably to the oracle…

Statistics Theory · Mathematics 2024-01-03 Laura Hucker , Martin Wahl

There is a known best possible upper bound on the probability of undetected error for linear codes. The $[n,k;q]$ codes with probability of undetected error meeting the bound have support of size $k$ only. In this note, linear codes of full…

Information Theory · Computer Science 2011-02-14 Torleiv Kløve , Jinquan Luo

We consider ensembles of channel codes that are partitioned into bins, and focus on analysis of exact random coding error exponents associated with optimum decoding of the index of the bin to which the transmitted codeword belongs. Two main…

Information Theory · Computer Science 2016-11-18 Neri Merhav

We establish an equivalence between two important random ensembles of linear codes: random linear codes (RLCs) and random Reed-Solomon (RS) codes. Specifically, we show that these models exhibit identical behavior with respect to key…

Information Theory · Computer Science 2025-11-17 Matan Levi , Jonathan Mosheiff , Nikhil Shagrithaya

We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in…

Machine Learning · Computer Science 2013-11-12 Spencer Greenberg , Mehryar Mohri

This work contains two main contributions concerning the expurgation of hierarchical ensembles for the asymmetric broadcast channel. The first is an analysis of the optimal maximum likelihood (ML) decoders for the weak and strong user. Two…

Information Theory · Computer Science 2017-11-29 Ran Averbuch , Nir Weinberger , Neri Merhav

Exponential error bounds for the finite-alphabet interference channel (IFC) with two transmitter-receiver pairs, are investigated under the random coding regime. Our focus is on optimum decoding, as opposed to heuristic decoding rules that…

Information Theory · Computer Science 2008-10-14 Raul Etkin , Neri Merhav , Erik Ordentlich

This paper studies the problem of distributionally robust model predictive control (MPC) using total variation distance ambiguity sets. For a discrete-time linear system with additive disturbances, we provide a conditional value-at-risk…

Systems and Control · Electrical Eng. & Systems 2022-06-27 Anushri Dixit , Mohamadreza Ahmadi , Joel W. Burdick
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