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In communication complexity-like problems, previous studies have shown either an exponential quantum advantage or an unbounded quantum advantage with an exponentially large input set $\Theta(2^{n})$ bits with respect to classical…

This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error…

Information Theory · Computer Science 2014-03-05 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

We study the complexity of high-dimensional approximation in the $L_2$-norm when different classes of information are available; we compare the power of function evaluations with the power of arbitrary continuous linear measurements. Here,…

Numerical Analysis · Mathematics 2023-03-23 David Krieg , Pawel Siedlecki , Mario Ullrich , Henryk Woźniakowski

Matrix product operators allow efficient descriptions (or realizations) of states on a 1D lattice. We consider the task of learning a realization of minimal dimension from copies of an unknown state, such that the resulting operator is…

Quantum Physics · Physics 2025-03-07 Marco Fanizza , Niklas Galke , Josep Lumbreras , Cambyse Rouzé , Andreas Winter

We study the gradient-based training of large-depth residual networks (ResNets) from standard random initializations. We show that infinite-depth ResNets behave as if they were infinitely wide, regardless of their actual width. More…

Machine Learning · Computer Science 2026-03-04 Lénaïc Chizat

We study the scaling of classification error rates with respect to the size of the training dataset. In contrast to classical results where rates are minimax optimal for a problem class, this work starts with the empirical observation that,…

Machine Learning · Statistics 2025-06-04 Pengkun Yang , Jingzhao Zhang

Discriminating between noisy quantum processes is a central primitive for quantum communication, metrology, and computing. While discrimination limits for finite-dimensional channels are well understood, the continuous-variable setting,…

Quantum Physics · Physics 2026-03-23 Zixin Huang , Ludovico Lami , Vishal Singh , Mark M. Wilde

In practical communication systems, knowledge of channel models is often absent, and consequently, transceivers need be designed based on empirical data. In this work, we study data-driven approaches to reliably choosing decoding metrics…

Information Theory · Computer Science 2024-04-23 Jiakun Liu , Wenyi Zhang , H. Vincent Poor

We establish theoretical guarantees for the expected prediction error of the exponential weighting aggregate in the case of multivariate regression that is when the label vector is multidimensional. We consider the regression model with…

Statistics Theory · Mathematics 2018-06-26 Arnak S. Dalalyan

We study near optimal error correction codes for real-time communication. In our setup the encoder must operate on an incoming source stream in a sequential manner, and the decoder must reconstruct each source packet within a fixed playback…

Information Theory · Computer Science 2013-05-16 Ahmed Badr , Ashish Khisti , Wai-Tian Tan , John Apostolopoulos

We study error exponents for the problem of relaying a message over a tandem of two channels sharing the same transition law, in particular moving beyond the 1-bit setting studied in recent related works. Our main results show that the…

Information Theory · Computer Science 2023-02-28 Yan Hao Ling , Jonathan Scarlett

This paper considers a binary channel with deletions and insertions, where each input bit is transformed in one of the following ways: it is deleted with probability d, or an extra bit is added after it with probability i, or it is…

Information Theory · Computer Science 2014-02-10 Ramji Venkataramanan , Sekhar Tatikonda , Kannan Ramchandran

We study the problem of consistently recovering the sparsity pattern of a regression parameter vector from correlated observations governed by deterministic missing data patterns using Lasso. We consider the case in which the observed…

Machine Learning · Computer Science 2022-06-13 Chuyang Ke , Jean Honorio

We study the problem of universal decoding for unknown discrete memoryless channels in the presence of erasure/list option at the decoder, in the random coding regime. Specifically, we harness a universal version of Forney's classical…

Information Theory · Computer Science 2017-06-23 Wasim Huleihel , Nir Weinberger , Neri Merhav

We consider channel coding for discrete memoryless channels (DMCs) with a novel cost constraint that constrains both the mean and the variance of the cost of the codewords. We show that the maximum (asymptotically) achievable rate under the…

Information Theory · Computer Science 2025-01-23 Adeel Mahmood , Aaron B. Wagner

Consider a binary-input memoryless output-symmetric channel $W$. Such a channel has a capacity, call it $I(W)$, and for any $R<I(W)$ and strictly positive constant $P_{\rm e}$ we know that we can construct a coding scheme that allows…

Information Theory · Computer Science 2016-11-17 S. Hamed Hassani , Kasra Alishahi , Rudiger Urbanke

In this paper, we study the Empirical Risk Minimization problem in the non-interactive local model of differential privacy. In the case of constant or low dimensionality ($p\ll n$), we first show that if the ERM loss function is $(\infty,…

Machine Learning · Computer Science 2018-05-18 Di Wang , Marco Gaboardi , Jinhui Xu

We present a finite blocklength performance bound for a DNA storage channel with insertions, deletions, and substitutions. The considered bound -- the dependency testing (DT) bound, introduced by Polyanskiy et al. in 2010 -- provides an…

Information Theory · Computer Science 2023-08-07 Issam Maarouf , Gianluigi Liva , Eirik Rosnes , Alexandre Graell i Amat

Error exponents characterize the exponential decay, when increasing message length, of the probability of error of many error-correcting codes. To tackle the long standing problem of computing them exactly, we introduce a general,…

Disordered Systems and Neural Networks · Physics 2007-07-16 Thierry Mora , Olivier Rivoire

We present an achievable rate for general deterministic relay networks, with broadcasting at the transmitters and interference at the receivers. In particular we show that if the optimizing distribution for the information-theoretic cut-set…

Information Theory · Computer Science 2007-10-24 A. S. Avestimehr , S. N. Diggavi , D. N. C. Tse
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