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In this paper, we consider the mixture of sparse linear regressions model. Let ${\beta}^{(1)},\ldots,{\beta}^{(L)}\in\mathbb{C}^n$ be $ L $ unknown sparse parameter vectors with a total of $ K $ non-zero coefficients. Noisy linear…

Information Theory · Computer Science 2018-08-03 Dong Yin , Ramtin Pedarsani , Yudong Chen , Kannan Ramchandran

Posterior matching uses variable-length encoding of the message controlled by noiseless feedback of the received symbols to achieve high rates for short average blocklengths. Traditionally, the feedback of a received symbol occurs before…

Information Theory · Computer Science 2024-04-16 Amaael Antonini , Rita Gimelshein , Richard D. Wesel

This paper proposes a binarization scheme for vectors of high dimension based on the recent concept of anti-sparse coding, and shows its excellent performance for approximate nearest neighbor search. Unlike other binarization schemes, this…

Computer Vision and Pattern Recognition · Computer Science 2011-10-27 Hervé Jégou , Teddy Furon , Jean-Jacques Fuchs

Neural network-based language models deal with data sparsity problems by mapping the large discrete space of words into a smaller continuous space of real-valued vectors. By learning distributed vector representations for words, each…

Computation and Language · Computer Science 2018-09-27 Davide Nunes , Luis Antunes

Network coding is a highly efficient data dissemination mechanism for wireless networks. Since network coded information can only be recovered after delivering a sufficient number of coded packets, the resulting decoding delay can become…

Information Theory · Computer Science 2016-11-17 Rui A. Costa , Daniele Munaretto , Joerg Widmer , Joao Barros

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

We propose a system for visual scene analysis and recognition based on encoding the sparse, latent feature-representation of an image into a high-dimensional vector that is subsequently factorized to parse scene content. The sparse feature…

Computer Vision and Pattern Recognition · Computer Science 2024-07-01 Christopher J. Kymn , Sonia Mazelet , Annabel Ng , Denis Kleyko , Bruno A. Olshausen

The capacity of unifilar finite-state channels in the presence of feedback is investigated. We derive a new evaluation method to extract graph-based encoders with their achievable rates, and to compute upper bounds to examine their…

Information Theory · Computer Science 2019-07-19 Oron Sabag , Bashar Huleihel , Haim Permuter

Point-to-multipoint communications are expected to play a pivotal role in next-generation networks. This paper refers to a cellular system transmitting layered multicast services to a multicast group of users. Reliability of communications…

Information Theory · Computer Science 2016-11-17 Andrea Tassi , Ioannis Chatzigeorgiou , Daniel E. Lucani

Index codes reduce the number of bits broadcast by a wireless transmitter to a number of receivers with different demands and with side information. It is known that the problem of finding optimal linear index codes is NP-hard. We…

Information Theory · Computer Science 2015-04-28 Xiao Huang , Salim El Rouayheb

Traditional distributed source coding rarely considers the possible link between separate encoders. However, the broadcast nature of wireless communication in sensor networks provides a free gossip mechanism which can be used to simplify…

Information Theory · Computer Science 2010-10-19 Zichong Chen , Guillermo Barrenetxea , Martin Vetterli

In the pliable variant of index coding, receivers are allowed to decode any new message not known a priori. Optimal code design for this variant involves identifying each receiver's choice of a new message that minimises the overall…

Information Theory · Computer Science 2022-05-06 Lawrence Ong , Badri N. Vellambi

Coded recurrent neural networks with three levels of sparsity are introduced. The first level is related to the size of messages, much smaller than the number of available neurons. The second one is provided by a particular coding rule,…

Machine Learning · Computer Science 2011-02-22 Vincent Gripon , Claude Berrou

This paper investigates variable-length stop-feedback codes for memoryless channels in point-to-point, multiple access, and random access communication scenarios. The proposed codes employ $L$ decoding times $n_1, n_2, \dots, n_L$ for the…

Information Theory · Computer Science 2023-12-12 Recep Can Yavas , Victoria Kostina , Michelle Effros

Compressive sensing has been successfully used for optimized operations in wireless sensor networks. However, raw data collected by sensors may be neither originally sparse nor easily transformed into a sparse data representation. This…

Networking and Internet Architecture · Computer Science 2016-08-16 Mohammad Abu Alsheikh , Shaowei Lin , Hwee-Pink Tan , Dusit Niyato

Recovery of the sparsity pattern (or support) of an unknown sparse vector from a small number of noisy linear measurements is an important problem in compressed sensing. In this paper, the high-dimensional setting is considered. It is shown…

Information Theory · Computer Science 2013-02-06 Galen Reeves , Michael Gastpar

We propose a simple yet effective wireless network coding and decoding technique. It utilizes spatial diversity through cooperation between nodes which carry out distributed encoding operations dictated by generator matrices of linear block…

Information Theory · Computer Science 2016-11-17 Tugcan Aktas , Ali Ozgur Yilmaz , Emre Aktas

We consider broadcasting a block of packets to multiple wireless receivers under random packet erasures using instantly decodable network coding (IDNC). The sender first broadcasts each packet uncoded once, then generates coded packets…

Information Theory · Computer Science 2016-01-20 Mingchao Yu , Parastoo Sadeghi , Neda Aboutorab

This paper focuses on a particular transmission scheme called local network coding, which has been reported to provide significant performance gains in practical wireless networks. The performance of this scheme strongly depends on the…

Networking and Internet Architecture · Computer Science 2015-03-17 Petteri Mannersalo , Georgios S. Paschos , Lazaros Gkatzikis

In a spiking neural network (SNN), individual neurons operate autonomously and only communicate with other neurons sparingly and asynchronously via spike signals. These characteristics render a massively parallel hardware implementation of…

Machine Learning · Computer Science 2017-05-17 Ping Tak Peter Tang , Tsung-Han Lin , Mike Davies