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» Learning Compressible Models
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DCC
2006
IEEE
15 years 9 months ago
Modeling Delta Encoding of Compressed Files
Abstract. The Compressed Delta Encoding paradigm is introduced, i.e., delta encoding directly in two given compressed files without decompressing. Here we explore the case where th...
Shmuel Tomi Klein, Tamar C. Serebro, Dana Shapira
ICIP
1999
IEEE
15 years 1 months ago
Forward Adaptive Modeling for Context-Based Compression of Large Binary Images in Applications Requiring Spatial Access
A method for compression of large binary images is proposed for applications where spatial access to the image is required. The proposed method is a two-stage combination of forwa...
Eugene I. Ageenko, Pasi Fränti
DCC
2009
IEEE
15 years 10 months ago
Compressed Kernel Perceptrons
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Slobodan Vucetic, Vladimir Coric, Zhuang Wang
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ICML
2008
IEEE
15 years 10 months ago
Compressed sensing and Bayesian experimental design
Matthias W. Seeger, Hannes Nickisch
DCC
2007
IEEE
15 years 4 months ago
Data Hiding based Compression Mechanism for 3D Models
: The paper proposes a lossy compression mechanism for 3D models (3D meshes) by improving existing compression mechanism such as progressive meshes and single refinement mesh compr...
Hui Li, Parag Agarwal, Balakrishnan Prabhakaran