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PyAO: PyTorch-Based Memory-Efficient LLM Training on Ethernet-Interconnected Clusters. [PDF]

Sensors (Basel)
Kim D, Kim H, Ahn J, Park S.
europepmc   +1 more source

Foreword to the CommDat special virtual issue on the raw diffraction data workshop and microsymposia at IUCr2023. [PDF]

IUCrdata
Kroon-Batenburg LMJ.
europepmc   +1 more source

Analysis of the block size influence in lossy compression of digital images

Vid Rogić
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Compressive Sampling and Lossy Compression

IEEE Signal Processing Magazine, 2008
Recent results in compressive sampling have shown that sparse signals can be recovered from a small number of random measurements. This property raises the question of whether random measurements can provide an efficient representation of sparse signals in an information-theoretic sense.
Vivek K. Goyal, Alyson K. Fletcher, Sundeep Rangan   +2 more
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Lossy compression of active sources

2008 IEEE International Symposium on Information Theory, 2008
In computer vision, an active vision source is a sensor that explores its environment in an active way, deciding to investigate parts of the environment in greater depth based on what it currently sees. We study the problem of determining the rate required to compress the output of an active vision source to within a desired fidelity.
Hari Palaiyanur, Cheng Chang, Anant Sahai   +2 more
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Lossy compression of noisy images

IEEE Transactions on Image Processing, 1998
Noise degrades the performance of any image compression algorithm. This paper studies the effect of noise on lossy image compression. The effect of Gaussian, Poisson, and film-grain noise on compression is studied. To reduce the effect of the noise on compression, the distortion is measured with respect to the original image not to the input of the ...
Osama K. Al-Shaykh, Russell M. Mersereau
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Separation architectures for lossy compression

2015 IEEE Information Theory Workshop (ITW), 2015
High-performance Model-Code Separation (MCS) architectures for lossless compression are practically viable with graphical message-passing in the decoder. This paper extends separation architectures to lossy compression by constructing model-free but semantics-aware encoders and contributes a new inference-friendly low-density hashing quantizer (LDHQ ...
Ying-zong Huang, Gregory W. Wornell
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Lossy compression of palletized images

IEEE International Conference on Acoustics Speech and Signal Processing, 1993
The authors present an algorithm for lossy compression of palletized images which uses standard compression techniques (JPEG, or Joint Photographic Experts Group, and JBIG), and produces a palletized image at the decoder. The technique is applicable to both custom and universal palletized images, and achieves good decompressed image quality at bit ...
Yung Chen, Heidi Peterson, Walter Bender
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On lossy compression of binary matrices

2017 IEEE International Symposium on Information Theory (ISIT), 2017
We consider lossy compression of random binary matrices under distortion constraints that strive to preserve the structure of the matrix. Specifically, we assume that matrix elements are statistically independent (but not necessarily identically distributed), and that the worst case row/column average distortion is to be controlled.
Bustin, Ronit, Shayevitz, Ofer
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