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In this paper, we consider the rate-distortion-perception (RDP) trade-off for the lossy compression of a Bernoulli vector source, which is a finite collection of independent binary random variables. The RDP function quantifies in a way the…

Information Theory · Computer Science 2025-01-22 Praneeth Kumar Vippathalla , Mihai-Alin Badiu , Justin P. Coon

Phase retrieval (PR) is a popular research topic in signal processing and machine learning. However, its performance degrades significantly when the measurements are corrupted by noise or outliers. To address this limitation, we propose a…

Optimization and Control · Mathematics 2025-05-30 Jun Fan , Ailing Yan , Xianchao Xiu , Wanquan Liu

Lossy image coding is the art of computing that is principally bounded by the image's rate-distortion function. This bound, though never accurately characterized, has been approached practically via deep learning technologies in recent…

Information Theory · Computer Science 2025-01-22 Haotian Zhang , Dong Liu

This paper deals with rate distortion or source coding with fidelity criterion, in measure spaces, for a class of source distributions. The class of source distributions is described by a relative entropy constraint set between the true and…

Information Theory · Computer Science 2013-05-07 Farzad Rezaei , Charalambos D. Charalambous , Photios A. Stavrou

Quantum random variable, distortion operator are introduced based on canonical operators. As the lower bound of rate distortion, the entanglement information rate distortion is achieved by Gaussian map for Gaussian source. General Gaussian…

Quantum Physics · Physics 2007-05-23 Xiao-yu Chen

We establish the first information-theoretic limits for multimodal retrieval. Casting ranking as lossy source coding, we derive a single-letter rate-distortion function $R(D)$ for reciprocal-rank distortion and prove a converse bound that…

Information Theory · Computer Science 2025-09-16 Thomas Y. Chen

We consider the problem of robust deconvolution, and particularly the recovery of an unknown deterministic signal convolved with a known filter and corrupted by additive noise. We present a novel, non-iterative data-driven approach.…

Signal Processing · Electrical Eng. & Systems 2021-11-04 Amir Weiss , Boaz Nadler

In this paper, random coding error exponents and cutoff rate are studied for noncoherent Rician fading channels, where neither the receiver nor the transmitter has channel side information. First, it is assumed that the input is subject…

Information Theory · Computer Science 2016-11-18 Mustafa Cenk Gursoy

Efficient lossless coding of medical volume data with temporal axis can be achieved by motion compensated wavelet lifting. As side benefit, a scalable bit stream is generated, which allows for displaying the data at different resolution…

Image and Video Processing · Electrical Eng. & Systems 2023-02-03 Daniela Lanz , André Kaup

In a setting where $m$ items need to be partitioned among $n$ agents, we evaluate the performance of mechanisms that take as input each agent's \emph{ordinal preferences}, i.e., their ranking of the items from most- to least-preferred. The…

Computer Science and Game Theory · Computer Science 2026-02-13 Ioannis Caragiannis , Vasilis Gkatzelis , Sebastian Homrighausen

The "water-filling" solution for the quadratic rate-distortion function of a stationary Gaussian source is given in terms of its power spectrum. This formula naturally lends itself to a frequency domain "test-channel" realization. We…

Information Theory · Computer Science 2008-02-18 Ram Zamir , Yuval Kochman , Uri Erez

I introduce rate-distortion theory for quantum coding, and derive a lower bound, involving the coherent information, on the rate at which qubits must be used to encode a quantum source with a given maximum level of distortion per source…

Quantum Physics · Physics 2007-05-23 Howard Barnum

One-bit quantization with time-varying sampling thresholds (also known as random dithering) has recently found significant utilization potential in statistical signal processing applications due to its relatively low power consumption and…

Information Theory · Computer Science 2024-01-17 Arian Eamaz , Farhang Yeganegi , Deanna Needell , Mojtaba Soltanalian

We present a novel systematic theoretical framework to analyze the rate-distortion (R-D) limits of learned image compression. While recent neural codecs have achieved remarkable empirical results, their distance from the…

Information Theory · Computer Science 2026-01-15 Changshuo Wang , Zijian Liang , Kai Niu , Ping Zhang

To improve the efficiency of Monte Carlo estimation, practitioners are turning to biased Markov chain Monte Carlo procedures that trade off asymptotic exactness for computational speed. The reasoning is sound: a reduction in variance due to…

Machine Learning · Statistics 2019-01-03 Jackson Gorham , Lester Mackey

The formalism of Wiener filtering is developed here for the purpose of reconstructing the large scale structure of the universe from noisy, sparse and incomplete data. The method is based on a linear minimum variance solution, given data…

Astrophysics · Physics 2009-10-22 S. Zaroubi , Y. Hoffman , K. B. Fisher , O. Lahav

We study a controlled version of the Bayesian sequential testing problem for the drift of a Wiener process, in which the observer exercises discretion over the signal intensity. This control incurs a running cost that reflects the resource…

Optimization and Control · Mathematics 2025-09-24 Steven Campbell , Georgy Gaitsgori , Richard Groenewald

In this paper, we consider the mismatched rate-distortion problem, in which the encoding is done using a codebook, and the encoder chooses the minimum-distortion codeword according to a mismatched distortion function that differs from the…

Information Theory · Computer Science 2022-12-20 Millen Kanabar , Jonathan Scarlett

In this thesis, I reflect on quantum instruments that measure the state of pure finite dimensional quantum systems. As the Heisenberg principle dictates, there exists a joint restriction to the information gain and distortion by measurement…

Quantum Physics · Physics 2007-05-23 Thijs van der Valk

Upon compressing perceptually relevant signals, conventional quantization generally results in unnatural outcomes at low rates. We propose distribution preserving quantization (DPQ) to solve this problem. DPQ is a new quantization concept…

Information Theory · Computer Science 2011-08-19 Minyue Li , Janusz Klejsa , W. Bastiaan Kleijn