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Compressive Sensing in Quantum Chemistry: A Little Computation Goes a Long Way

Gregory J. O. Beran
2015 ACS Central Science  
This progress stems from massive gains in computer hardware, advances in physical models (effective density functionals, for example), and creative numerical algorithms that maximize the efficiency with  ...  The exploitation of inherent sparsity, or the pattern of zeros or near-zero terms in a matrix, is a common theme in many of these numerical algorithms.  ...  This progress stems from massive gains in computer hardware, advances in physical models (effective density functionals, for example), and creative numerical algorithms that maximize the efficiency with  ... 
doi:10.1021/acscentsci.5b00062 pmid:27162940 pmcid:PMC4827478 fatcat:ohlyhwtmsnbdvdzhji4vafkzsy

An Adaptive Difference Distribution-Based Coding with Hierarchical Tree Structure for DNA Sequence Compression

Wenrui Dai, Hongkai Xiong, Xiaoqian Jiang, L. Ohno-Machado
2013 2013 Data Compression Conference  
Previous reference-based compression on DNA sequences do not fully exploit the intrinsic statistics by merely concerning the approximate matches.  ...  To keep the distribution of difference sequence from the reference and target sequences concentrated, the sub-fragment size and matching offset for predicting are flexible to the stepped size structure  ...  The compression performance was improved in successive literatures by the introduction of Markov model for non-repeated regions [4] , extension to the approximate repeats for further exploitation of the  ... 
doi:10.1109/dcc.2013.45 pmid:26501129 pmcid:PMC4617277 dblp:conf/dcc/DaiXJO13 fatcat:wllx4iysqvai3bupphd6rnuld4

Semantic Database Compression System Based on Augmented Vector Quantization

Saad M. Darwish
2015 Journal of Software  
In this paper, we propose a database compression system that takes advantage of attributes semantics and data-mining models to find frequent attribute pattern with maximum gain to perform compression of  ...  massive table's data.  ...  In this paper we have described a novel database compression system that exploits attribute semantics and data-mining model to effectively compress massive data tables.  ... 
doi:10.17706//jsw.10.10.1127-113 fatcat:kehfuca3snbrnjbf3eac4oujc4

Semantic Database Compression System Based on Augmented Vector Quantization

Saad M. Darwish, Saleh M. El-Kaffas, Omar A. Abdulateef
2015 Journal of Software  
In this paper, we propose a database compression system that takes advantage of attributes semantics and data-mining models to find frequent attribute pattern with maximum gain to perform compression of  ...  massive table's data.  ...  In this paper we have described a novel database compression system that exploits attribute semantics and data-mining model to effectively compress massive data tables.  ... 
doi:10.17706/jsw.10.10.1127-1139 fatcat:aefessqb2jh6nlxrh245cnafei

Technical strategies for massive model visualization

Enrico Gobbetti, Dave Kasik, Sung-eui Yoon
2008 Proceedings of the 2008 ACM symposium on Solid and physical modeling - SPM '08  
Figure 1 : Examples of massive models.  ...  We argue that developing efficient data access and data management techniques is key in solving the problem of interactive visualization of massive models.  ...  This work was partially supported by: the Italian Ministry of University and Research under grant CYBERSAR; a KAIST seed grant; the MIC, under grant "Development of Elemental Technology for Promoting Digital  ... 
doi:10.1145/1364901.1364960 dblp:conf/sma/GobbettiKY08 fatcat:t65dyj6jrfcgrjivf2od4ok6cq

Technical strategies for massive model visualization

Enrico Gobbetti, Dave Kasik, Sung-eui Yoon
2008 ACM SIGGRAPH ASIA 2008 courses on - SIGGRAPH Asia '08  
Figure 1 : Examples of massive models.  ...  We argue that developing efficient data access and data management techniques is key in solving the problem of interactive visualization of massive models.  ...  This work was partially supported by: the Italian Ministry of University and Research under grant CYBERSAR; a KAIST seed grant; the MIC, under grant "Development of Elemental Technology for Promoting Digital  ... 
doi:10.1145/1508044.1508073 fatcat:5zkxt75corampkusiaylcxdsva

Deep Learning for Massive MIMO Channel State Acquisition and Feedback [article]

Mahdi Boloursaz Mashhadi, Deniz Gündüz
2020 arXiv   pre-print
with high spectral and energy efficiency.  ...  Recently, deep learning (DL)-based approaches for massive MIMO training have been proposed and showed significant improvements compared to traditional techniques.  ...  Hence, more insights on the correlation structures of the CSI in practical massive MIMO systems need to be exploited to design more efficient and less complex NNs for the CSI acquisition tasks.  ... 
arXiv:2002.06945v3 fatcat:rsrkcgdq5rabvf5gmftabna6va

Bayesian compressed sensing-based channel estimation for massive MIMO systems

Hayder Al-Salihi, Mohammad Reza Nakhai
2016 2016 European Conference on Networks and Communications (EuCNC)  
is therefore proposed for the uplink of multi-user massive MIMO systems.  ...  The efficient and highly accurate channel state information (CSI) at the base station is essential to achieve the potential benefits of massive multiple input multiple output (MIMO) orthogonal frequency  ...  MASSIVE MIMO SYSTEM MODEL Following the system model of [11] and [6] with modification, we consider a multi-cell massive MIMO-OFDM system with C cells.  ... 
doi:10.1109/eucnc.2016.7561063 dblp:conf/eucnc/Al-SalihiN16 fatcat:kgwhdkjhjfftjp4grrhyxfwcua

Deep Learning for Massive MIMO Channel State Acquisition and Feedback

Mahdi Boloursaz Mashhadi, Deniz Gündüz
2020 Journal of the Indian Institute of Science  
with high spectral and energy efficiency.  ...  In this paper, we present an overview of the state-of-the-art DL architectures and algorithms used for CSI acquisition and feedback, and provide further research directions.  ...  Hence, more insights on the correlation structures of the CSI in practical massive MIMO systems need to be exploited to design more efficient and less complex NNs for the CSI acquisition tasks.  ... 
doi:10.1007/s41745-020-00169-2 pmid:32624647 pmcid:PMC7319300 fatcat:wau7u3ennvgv3eauhlk46gawr4

Massive Access for Future Wireless Communication Systems [article]

Yongpeng Wu, Xiqi Gao, Shidong Zhou, Wei Yang, Yury Polyanskiy, and Giuseppe Caire
2020 arXiv   pre-print
, the design of low complexity and energy-efficient massive access coding and communication schemes, efficient methods for the detection of a relatively small number of active users among a large number  ...  of potential user devices with sporadic transmission pattern, and the integration of massive access with massive MIMO and other important wireless communication technologies.  ...  By exploiting this sporadic traffic, a compressive sensing-based scheme is proposed to detect user activity and estimate the channels for massive access in massive MIMO systems [25] .  ... 
arXiv:1910.12678v5 fatcat:qnc3vxft65adlpmfnd4j7nhkza

RasterZip

Francesco Fusco, Michail Vlachos, Xenofontas Dimitropoulos
2012 Proceedings of the 2012 ACM conference on Internet measurement conference - IMC '12  
of massive datasets.  ...  However, present solutions are tied to generalpurpose compressors, which do not exploit patterns of network traffic data and require to decompress a lot of redundant data for high selectivity queries.  ...  For this reason, an increasing number of applications need to efficiently search massive network traffic archives.  ... 
doi:10.1145/2398776.2398783 dblp:conf/imc/FuscoVD12 fatcat:okm6lfs2lfde5axrh2sajb4yom

A Survey on Data Compression Methods for Biological Sequences

Morteza Hosseini, Diogo Pratas, Armando Pinho
2016 Information  
Finally, we present some suggestions for future research on biological data compression.  ...  In this paper, we provide a comprehensive survey of existing compression approaches, that are specialized for biological data, including protein and DNA sequences.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/info7040056 fatcat:khkh5h6425adpdcojg2b7zudjy

Decoupling Channel Estimation for FDD Massive MIMO Systems Utilizing Joint Sparsity

Xiangyu Yan, Li Chen, Huarui Yin, Weidong Wang
2020 IEEE Access  
Effective channel estimation for massive multiple-input-multiple-output (MIMO) systems based on frequency division duplex (FDD) protocol is a crucial problem.  ...  INDEX TERMS Angle domain, channel estimation, compressive sensing, delay domain, massive multiple-input-multiple-output, pilot design, sparsity.  ...  By exploiting the channel sparsity, CS-based channel estimation with non-orthogonal pilot design can provide the efficient compression and reliable recovery of the sparse channel matrix.  ... 
doi:10.1109/access.2020.2991084 fatcat:h72suy5rtfgsxobykqv3c67hdq

Massively-Parallel Lossless Data Decompression [article]

Evangelia Sitaridi, Rene Mueller, Tim Kaldewey, Guy Lohman, Kenneth Ross
2016 arXiv   pre-print
Although research has concentrated on efficient compression, fast decompression is critical for analytics queries that repeatedly read compressed data.  ...  We propose two new techniques to increase the degree of parallelism during decompression. The first technique exploits the massive parallelism of GPU and SIMD architectures.  ...  The first technique exploits the SIMD-like execution model of GPUs to coordinate the threads that are concurrently decompressing a data block.  ... 
arXiv:1606.00519v1 fatcat:ywu6e6zrbrcvrdecrgnn7acd7a

Lossless Image Compression through Super-Resolution [article]

Sheng Cao, Chao-Yuan Wu, Philipp Krähenbühl
2020 arXiv   pre-print
We introduce a simple and efficient lossless image compression algorithm. We store a low resolution version of an image as raw pixels, followed by several iterations of lossless super-resolution.  ...  For lossless super-resolution, we predict the probability of a high-resolution image, conditioned on the low-resolution input, and use entropy coding to compress this super-resolution operator.  ...  Related Work Most lossless image compression algorithms rely on entropy coding of commonly repeating image patterns.  ... 
arXiv:2004.02872v1 fatcat:ocwhfs5f55ht3o2dc3w3lfkcbe
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