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A receiver wants to compute a function of two correlated sources separately observed by two transmitters. One of the transmitters may send a possibly private message to the other transmitter in a cooperation phase before both transmitters…

Information Theory · Computer Science 2015-04-08 Milad Sefidgaran , Aslan Tchamkerten

We define a graph-based rate optimization problem and consider its computation, which provides a unified approach to the computation of various theoretical limits, including the (conditional) graph entropy, rate-distortion functions and…

Information Theory · Computer Science 2025-03-18 Deheng Yuan , Tao Guo , Zhongyi Huang , Shi Jin

We describe a general technique that yields the first {\em Statistical Query lower bounds} for a range of fundamental high-dimensional learning problems involving Gaussian distributions. Our main results are for the problems of (1) learning…

Machine Learning · Computer Science 2017-05-18 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

Increasingly, visual signals such as images, videos and point clouds are being captured solely for the purpose of automated analysis by computer vision models. Applications include traffic monitoring, robotics, autonomous driving, smart…

Image and Video Processing · Electrical Eng. & Systems 2025-07-25 Ivan V. Bajić

We consider the one helper source coding problem posed and investigated by Ahlswede, K\"orner and Wyner. In this system, the error probability of decoding goes to one as the source block length $n$ goes to infinity. This implies that we…

Information Theory · Computer Science 2019-01-18 Yasutada Oohama

We conduct a study of graphical models and discuss the quality of model selection approximation by formulating the problem as a detection problem and examining the area under the curve (AUC). We are specifically looking at the model…

Information Theory · Computer Science 2016-08-26 Navid Tafaghodi Khajavi , Anthony Kuh

We prove the strong converse for the $N$-source Gaussian multiple access channel (MAC). In particular, we show that any rate tuple that can be supported by a sequence of codes with asymptotic average error probability less than one must lie…

Information Theory · Computer Science 2016-10-19 Silas L. Fong , Vincent Y. F. Tan

This paper presents a novel method to determine rate-distortion optimized transform coefficients for efficient compression of videos generated from point clouds. The method exploits a generalized frequency selective extrapolation approach…

Image and Video Processing · Electrical Eng. & Systems 2022-06-27 Christian Herglotz , Nils Genser , André Kaup

A coding scheme with scalar lattices is applied to K-receiver, Gaussian, vector broadcast channels with K independent messages, one for each receiver. The method decomposes each receiver channel into parallel scalar channels with known…

Information Theory · Computer Science 2024-04-25 M. Yusuf Şener , Gerhard Kramer , Shlomo Shamai , Ronald Böhnke , Wen Xu

A secrecy system with side information at the decoders is studied in the context of lossy source compression over a noiseless broadcast channel. The decoders have access to different side information sequences that are correlated with the…

Information Theory · Computer Science 2014-10-07 Eva C. Song , Paul Cuff , H. Vincent Poor

In this paper, we investigate the optimal tradeoff between source and channel coding for channels with bit or packet erasure. Upper and Lower bounds on the optimal channel coding rate are computed to achieve minimal end-to-end distortion.…

Information Theory · Computer Science 2007-07-13 Sriram N. Kizhakkemadam , Panos Papamichalis , Mandyam Srinath , Dinesh Rajan

This paper studies the minimum achievable source coding rate as a function of blocklength $n$ and probability $\epsilon$ that the distortion exceeds a given level $d$. Tight general achievability and converse bounds are derived that hold at…

Information Theory · Computer Science 2016-11-15 Victoria Kostina , Sergio Verdú

In this paper, we study the computation of the rate-distortion-perception function (RDPF) for a multivariate Gaussian source under mean squared error (MSE) distortion and, respectively, Kullback-Leibler divergence, geometric Jensen-Shannon…

Information Theory · Computer Science 2023-11-16 Giuseppe Serra , Photios A. Stavrou , Marios Kountouris

We consider the transmission of a memoryless bivariate Gaussian source over an average-power-constrained one-to-two Gaussian broadcast channel. The transmitter observes the source and describes it to the two receivers by means of an…

Information Theory · Computer Science 2009-03-20 Shraga Bross , Amos Lapidoth , Stephan Tinguely

This paper investigates the rate-distortion function, under a squared error distortion $D$, for an $n$-dimensional random vector uniformly distributed on an $(n-1)$-sphere of radius $R$. First, an expression for the rate-distortion function…

Information Theory · Computer Science 2024-01-10 Alex Dytso , Martina Cardone

This paper investigates the best known bounds on the quadratic Gaussian distortion-rate-perception function with limited common randomness for the Kullback-Leibler divergence-based perception measure, as well as their counterparts for the…

Information Theory · Computer Science 2024-09-05 Li Xie , Liangyan Li , Jun Chen , Lei Yu , Zhongshan Zhang

We present the first unified framework for rate-distortion-optimized compression and segmentation of 3D Gaussian Splatting (3DGS). While 3DGS has proven effective for both real-time rendering and semantic scene understanding, prior works…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Yu-Jen Tseng , Chia-Hao Kao , Jing-Zhong Chen , Alessandro Gnutti , Shao-Yuan Lo , Yen-Yu Lin , Wen-Hsiao Peng

In this paper, distributed (or multiterminal) source coding with one distortion criterion and correlated messages is considered. This problem can be also called ``Berger-Yeung problem with correlated messages''. It corresponds to the source…

Information Theory · Computer Science 2009-08-18 Suhan Choi

This article is in the context of gradient compression. Gradient compression is a popular technique for mitigating the communication bottleneck observed when training large machine learning models in a distributed manner using…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-24 Tharindu Adikari

We consider the problem of encoding a finite set of vectors into a small number of bits while approximately retaining information on the angular distances between the vectors. By deriving improved variance bounds related to binary Gaussian…

Information Theory · Computer Science 2017-12-27 Sjoerd Dirksen , Alexander Stollenwerk
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