Results 31 to 40 of about 22,970,744 (375)
Optimization of Microarchitecture and Dataflow for Sparse Tensor CNN Acceleration
IEEE Access, 2023 The inherent sparsity present in convolutional neural networks (CNNs) offers a valuable opportunity to significantly decrease the computational workload during inference.
Ngoc-Son Pham, Taeweon Suh
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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
semanticscholar +1 more source
Journal of Digital Imaging, 1997 The tutorial will expand on all of the topics outlined above and will provide additional information on other compression techniques. The practical implications of data compression and the important considerations in choosing a compression scheme will also be discussed.
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Data Compression for Climate Data [PDF]
Supercomputing Frontiers and Innovations, 2016 The different rates of increase for computational power and storage capabilities of supercomputers turn data storage into a technical and economical problem. Because storage capabilities are lagging behind, investments and operational costs for storage systems have increased to keep up with the supercomputers' I/O requirements.
Michael Kuhn +2 more
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IEEE Access, 2021 Data compression is an important part of information security because compressed data is more secure and easy to handle. Effective data compression technology creates efficient, secure, and easy-to-connect data.
Osama Fouad Abdel Wahab +3 more
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DeepZip: Lossless Data Compression Using Recurrent Neural Networks [PDF]
Data Compression Conference, 2018 Sequential data is being generated at an unprecedented pace in various forms, including text and genomic data. This creates the need for efficient compression mechanisms to enable better storage, transmission and processing of such data.
Mohit Goyal +3 more
semanticscholar +1 more source
One-shot lossy quantum data compression [PDF]
, 2013 We provide a framework for one-shot quantum rate distortion coding, in which the goal is to determine the minimum number of qubits required to compress quantum information as a function of the probability that the distortion incurred upon decompression ...
Datta, Nilanjana +3 more
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Multi-Dimensional Data Compression and Query Processing in Array Databases
IEEE Access, 2022 In recent times, the production of multidimensional data in various domains and their storage in array databases has witnessed a sharp increase; this rapid growth in data volumes necessitates compression in array databases.
Minsoo Kim, Hyubjin Lee, Yon Dohn Chung
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BtrBlocks: Efficient Columnar Compression for Data Lakes
Proc. ACM Manag. Data, 2023 Analytics is moving to the cloud and data is moving into data lakes. These reside on object storage services like S3 and enable seamless data sharing and system interoperability.
Maximilian Kuschewski +3 more
semanticscholar +1 more source
The relative efficiency of data compression by LZW and LZSS
Data Science Journal, 2007 We explore the use of the LZW and LZSS data compression methods. These methods or some versions of them are very common in use of compressing different types of data.
Yair Wiseman
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