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The maximum a-posteriori (MAP) perturbation framework has emerged as a useful approach for inference and learning in high dimensional complex models. By maximizing a randomly perturbed potential function, MAP perturbations generate unbiased…

Machine Learning · Computer Science 2013-10-17 Francesco Orabona , Tamir Hazan , Anand D. Sarwate , Tommi Jaakkola

The common approach of designing a communication device is to maximize a well-defined objective function, e.g., the channel capacity and the cut-off rate. We propose easy-to-implement solutions for Gaussian channels that approximate the…

Information Theory · Computer Science 2016-03-24 Qian Yu

Many Bayesian statistical inference problems come down to computing a maximum a-posteriori (MAP) assignment of latent variables. Yet, standard methods for estimating the MAP assignment do not have a finite time guarantee that the algorithm…

Machine Learning · Statistics 2024-10-31 Harsh Vardhan Dubey , Ji Ah Lee , Patrick Flaherty

We recently showed in [1] the superiority of certain structured coding matrices ensembles (such as partial row-orthogonal) for sparse superposition codes when compared with purely random matrices with i.i.d. entries, both…

Information Theory · Computer Science 2022-07-12 YuHao Liu , Teng Fu , Jean Barbier , TianQi Hou

This paper considers a binary channel with deletions. We derive two close form upper bound on the capacity of binary deletion channel. The first upper bound is based on computing the capacity of an auxiliary channel and we show how the…

Information Theory · Computer Science 2021-03-23 Hassan Tavakoli

In this paper, we consider the amplified-and-forward relaying in an OFDM system with unitary linear processing at the relay. We proposed a general analytical framework to find the unitary linear processing matrix that maximizes the system…

Information Theory · Computer Science 2012-04-27 Min Dong , Mahdi Hajiaghayi , Ben Liang

We analyze the quantum capacity of a unital quantum channel, using ideas from the proof of near-optimality of Petz recovery map [Barnum and Knill 2000] and give an upper bound on the quantum capacity in terms of regularized output $2$-norm…

Quantum Physics · Physics 2018-03-07 Anurag Anshu

We consider transmission over a binary-input additive white Gaussian noise channel using low-density parity-check codes. One of the most popular techniques for decoding low-density parity-check codes is the linear programming decoder. In…

Information Theory · Computer Science 2015-03-19 Shrinivas Kudekar , Jason K. Johnson , Misha Chertkov

The mutual information is bounded from above by a decreasing affine function of the square of the distance between the input distribution and the set of all capacity-achieving input distributions $\Pi_{\mathcal{A}}$, on small enough…

Information Theory · Computer Science 2025-04-24 Barış Nakiboğlu , Hao-Chung Cheng

The Bayesian framework is ideally suited for induction problems. The probability of observing $x_t$ at time $t$, given past observations $x_1...x_{t-1}$ can be computed with Bayes' rule if the true distribution $\mu$ of the sequences…

Artificial Intelligence · Computer Science 2011-11-09 Marcus Hutter

Recent studies have revealed a number of pathologies of neural machine translation (NMT) systems. Hypotheses explaining these mostly suggest there is something fundamentally wrong with NMT as a model or its training algorithm, maximum…

Computation and Language · Computer Science 2020-10-29 Bryan Eikema , Wilker Aziz

We consider a setting of Slepian--Wolf coding, where the random bin of the source vector undergoes channel coding, and then decoded at the receiver, based on additional side information, correlated to the source. For a given distribution of…

Information Theory · Computer Science 2016-01-26 Neri Merhav

We study a class of binary detection problems involving a single fusion center and a large or countably infinite number of sensors. Each sensor acts under a decentralized information structure, accessing only a local noisy observation…

Optimization and Control · Mathematics 2025-09-29 Sina Sanjari , Naci Saldi , Sinan Gezici , Serdar Yüksel

In this paper, we investigate the robust linear precoder design for three dimensional (3D) massive multi-input multi-output (MIMO) downlink with uniform planar array (UPA) and imperfect channel state information (CSI). In practical massive…

Information Theory · Computer Science 2022-06-17 An-An Lu , Xiqi Gao , Chengshan Xiao

The problem of channel shortening equalization for optimal detection in ISI channels is considered. The problem is to choose a linear equalizer and a partial response target filter such that the combination produces the best detection…

Information Theory · Computer Science 2007-10-23 Raman Venkataramani , M. Fatih Erden

Binary classifiers trained on a certain proportion of positive items introduce a bias when applied to data sets with different proportions of positive items. Most solutions for dealing with this issue assume that some information on the…

Machine Learning · Statistics 2021-02-18 Marco J. H. Puts , Piet J. H. Daas

Modern wireless channels are increasingly dense and mobile making the channel highly non-stationary. The time-varying distribution and the existence of joint interference across multiple degrees of freedom (e.g., users, antennas, frequency…

Information Theory · Computer Science 2022-11-14 Zhibin Zou , Maqsood Careem , Aveek Dutta , Ngwe Thawdar

We determine the optimal rates of universal quantum codes for entanglement transmission and generation under channel uncertainty. In the simplest scenario the sender and receiver are provided merely with the information that the channel…

Quantum Physics · Physics 2015-05-13 I. Bjelakovic , H. Boche , J. Noetzel

We investigate the binary-symmetric parallel-relay network where there is one source, one destination, and multiple relays in parallel. We show that forwarding relays, where the relays merely transmit their received signals, achieve the…

Information Theory · Computer Science 2014-03-11 Lawrence Ong , Sarah J. Johnson , Christopher M. Kellett

Undersampled inverse problems occur everywhere in the sciences including medical imaging, radar, astronomy etc., yielding underdetermined linear or non-linear reconstruction problems. There are now a myriad of techniques to design decoders…

Optimization and Control · Mathematics 2023-11-29 Nina Maria Gottschling , Paolo Campodonico , Vegard Antun , Anders C. Hansen
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