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We consider the remote vector source coding problem in which a vector Gaussian source is to be estimated from noisy linear measurements. For this problem, we derive the performance of the compress-and-estimate (CE) coding scheme and compare…

Information Theory · Computer Science 2017-07-04 Ruiyang Song , Stefano Rini , Alon Kipnis , Andrea Goldsmith

Future beyond-5G and 6G systems demand ultra-reliable, low-latency communication with short blocklengths, motivating the development of universal decoding algorithms. Guessing decoding, which infers the noise or codeword candidate in order…

Information Theory · Computer Science 2025-11-24 Qianfan Wang , Jifan Liang , Peihong Yuan , Ken R. Duffy , Muriel Médard , Xiao Ma

This paper introduces Relative Predictive Coding (RPC), a new contrastive representation learning objective that maintains a good balance among training stability, minibatch size sensitivity, and downstream task performance. The key to the…

Machine Learning · Computer Science 2021-04-14 Yao-Hung Hubert Tsai , Martin Q. Ma , Muqiao Yang , Han Zhao , Louis-Philippe Morency , Ruslan Salakhutdinov

In near-term quantum computations that do not employ error correction, noise can proliferate rapidly, corrupting the quantum state and making results unreliable. These errors originate from both decoherence and control imprecision. The…

The Shortest Common Superstring (SCS) problem asks for the shortest string that contains each of a given set of strings as a substring. Its reverse-complement variant, the Shortest Common Superstring problem with Reverse Complements…

Data Structures and Algorithms · Computer Science 2026-01-23 Ryosuke Yamano , Tetsuo Shibuya

Fundamental rate-distortion-perception (RDP) trade-offs arise in applications requiring maintained perceptual quality of reconstructed data, such as neural image compression. When compressed data is transmitted over public communication…

Information Theory · Computer Science 2026-04-23 Gustaf Åhlgren , Onur Günlü

One of the key issues in the acquisition of sparse data by means of compressed sensing (CS) is the design of the measurement matrix. Gaussian matrices have been proven to be information-theoretically optimal in terms of minimizing the…

Information Theory · Computer Science 2018-11-26 Ahmed Elzanaty , Andrea Giorgetti , Marco Chiani

A three terminal relay system with binary erasure channel (BEC) was considered, in which a source forwarded information to a destination with a relay's "assistance". The nested LDGM (Low-density generator-matrix) -LDPC (low-density…

Information Theory · Computer Science 2010-03-22 Zheng Bingbing , Jiang Lingge , He Chen , Wang Qingchuan

Submodular maximization under matroid constraints is a fundamental problem in combinatorial optimization with applications in sensing, data summarization, active learning, and resource allocation. While the Sequential Greedy (SG) algorithm…

Machine Learning · Computer Science 2026-05-20 Mohammadreza Rostami , Solmaz S. Kia

This paper considers the problem of implementing large-scale gradient descent algorithms in a distributed computing setting in the presence of {\em straggling} processors. To mitigate the effect of the stragglers, it has been previously…

Machine Learning · Statistics 2019-01-04 Raj Kumar Maity , Ankit Singh Rawat , Arya Mazumdar

Consider a lossy compression system with $\ell$ distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under…

Information Theory · Computer Science 2018-07-19 Yizhong Wang , Li Xie , Xuan Zhang , Jun Chen

In a modern distributed storage system, storage nodes are organized in racks, and the cross-rack communication dominates the system bandwidth. In We study the rack-aware storage system where all storage nodes are organized in racks and…

Information Theory · Computer Science 2022-07-18 Liyang Zhou , Zhifang Zhang

The coordinate descent (CD) method has recently become popular for solving very large-scale problems, partly due to its simple update, low memory requirement, and fast convergence. In this paper, we explore the greedy CD on solving…

Optimization and Control · Mathematics 2020-12-14 Chenyu Wu , Yangyang Xu

A random access code (RAC) is a strategy to encode a message into a shorter one in a way that any bit of the original can still be recovered with nontrivial probability. Encoding with quantum bits rather than classical ones can improve this…

Quantum Physics · Physics 2020-08-21 Giulio Foletto , Luca Calderaro , Giuseppe Vallone , Paolo Villoresi

The total effective resistance, also called the Kirchhoff index, provides a robustness measure for a graph $G$. We consider two optimization problems of adding $k$ new edges to $G$ such that the resulting graph has minimal total effective…

Social and Information Networks · Computer Science 2023-09-18 Maria Predari , Lukas Berner , Robert Kooij , Henning Meyerhenke

In this work we propose RELDEC, a novel approach for sequential decoding of moderate length low-density parity-check (LDPC) codes. The main idea behind RELDEC is that an optimized decoding policy is subsequently obtained via reinforcement…

Information Theory · Computer Science 2023-07-28 Salman Habib , Allison Beemer , Joerg Kliewer

We propose a mechanism that incorporates network coding into TCP with only minor changes to the protocol stack, thereby allowing incremental deployment. In our scheme, the source transmits random linear combinations of packets currently in…

Networking and Internet Architecture · Computer Science 2016-11-17 Jay Kumar Sundararajan , Devavrat Shah , Muriel Medard , Michael Mitzenmacher , Joao Barros

In this work, we propose a cross-layer design strategy based on the parallel interference cancellation (PIC) detection technique and a multi-relay selection algorithm for the uplink of cooperative direct-sequence code-division multiple…

Information Theory · Computer Science 2014-06-03 J. Gu , R. C. de Lamare

The recently developed matrix based Renyi's entropy enables measurement of information in data simply using the eigenspectrum of symmetric positive semi definite (PSD) matrices in reproducing kernel Hilbert space, without estimation of the…

Machine Learning · Statistics 2023-01-10 Tieliang Gong , Yuxin Dong , Shujian Yu , Bo Dong

Quantum reservoir computing (QRC) is a promising quantum machine learning framework for near-term quantum platforms, yet the performance of different QRC architectures under realistic constraints remains largely unexplored. Here, we provide…

Quantum Physics · Physics 2026-04-03 Dong-Sheng Liu , Qing-Xuan Jie , Chang-Ling Zou , Xi-Feng Ren , Guang-Can Guo