Results 21 to 30 of about 21,889,530 (328)
Efficient data compression in perception and perceptual memory.
Psychology Review, 2020 Efficient data compression is essential for capacity-limited systems, such as biological perception and perceptual memory. We hypothesize that the need for efficient compression shapes biological systems in many of the same ways that it shapes engineered
Christopher Bates, R. Jacobs
semanticscholar +1 more source
Data compression on the sphere [PDF]
Astronomy & Astrophysics, 2011 13 pages, 8 figures, accepted for publication by A&A; We make our SZIP program that implements these compression algorithms available publicly from http://www.szip.org ...
Yves Wiaux +5 more
openaire +3 more sources
Toward Bayesian Data Compression [PDF]
Annalen der Physik, 2021 AbstractIn order to handle large datasets omnipresent in modern science, efficient compression algorithms are necessary. Here, a Bayesian data compression (BDC) algorithm that adapts to the specific measurement situation is derived in the context of signal reconstruction.
Philipp Arras +6 more
openaire +4 more sources
Full-State Quantum Circuit Simulation by Using Data Compression [PDF]
International Conference for High Performance Computing, Networking, Storage and Analysis, 2019 Quantum circuit simulations are critical for evaluating quantum algorithms and machines. However, the number of state amplitudes required for full simulation increases exponentially with the number of qubits.
Xin-Chuan Wu +6 more
semanticscholar +1 more source
ACM Computing Surveys, 1987 This paper surveys a variety of data compression methods spanning almost 40 years of research, from the work of Shannon, Fano, and Huffman in the late 1940s to a technique developed in 1986. The aim of data compression is to reduce redundancy in stored or communicated data, thus increasing effective data density.
Lelewer, Debra A., Hirschberg, Daniel S.
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Data compression in cosmology: A compressed likelihood for Planck data [PDF]
Physical Review D, 2019 8 pages, 7 figures, accepted by Phys. Rev. D. For CosMOPED code see https://github.com/heatherprince/cosmoped; for Planck-lite-py see https://github.com/heatherprince/planck-lite ...
Heather Prince, Jo Dunkley
openaire +3 more sources
Time-Universal Data Compression
Algorithms, 2019 Nowadays, a variety of data-compressors (or archivers) is available, each of which has its merits, and it is impossible to single out the best ones. Thus, one faces the problem of choosing the best method to compress a given file, and this problem is ...
Boris Ryabko
doaj +1 more source
Stochastic Controlled Averaging for Federated Learning with Communication Compression [PDF]
International Conference on Learning Representations, 2023 Communication compression, a technique aiming to reduce the information volume to be transmitted over the air, has gained great interests in Federated Learning (FL) for the potential of alleviating its communication overhead.
Xinmeng Huang, Ping Li, Xiaoyun Li
semanticscholar +1 more source
Deep learning for in situ data compression of large turbulent flow simulations
, 2020 Large turbulent flow simulations can lead to information bottlenecks as data is generated faster than it can be processed and saved. Innovative in-situ data compression techniques are needed.
Andrew Glaws, R. King, M. Sprague
semanticscholar +1 more source
Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology [PDF]
, 2018 Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood ...
J. Alsing +2 more
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