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The Nature of Statistical Learning Theory
, 1999
"... Statistical learning theory was introduced in the late 1960’s. Until the 1990’s it was a purely theoretical analysis of the problem of function estimation from a given collection of data. In the middle of the 1990’s new types of learning algorithms (called support vector machines) based on the deve ..."
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Cited by 13236 (32 self)
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Statistical learning theory was introduced in the late 1960’s. Until the 1990’s it was a purely theoretical analysis of the problem of function estimation from a given collection of data. In the middle of the 1990’s new types of learning algorithms (called support vector machines) based
Maximum likelihood from incomplete data via the EM algorithm
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1977
"... A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situat ..."
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Cited by 11972 (17 self)
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A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value
A blocksorting lossless data compression algorithm
, 1994
"... We describe a blocksorting, lossless data compression algorithm, and our implementation of that algorithm. We compare the performance of our implementation with widely available data compressors running on the same hardware. The algorithm works by applying a reversible transformation to a block o ..."
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Cited by 809 (5 self)
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We describe a blocksorting, lossless data compression algorithm, and our implementation of that algorithm. We compare the performance of our implementation with widely available data compressors running on the same hardware. The algorithm works by applying a reversible transformation to a block
Text Data Compression Algorithms
, 1997
"... Contents 1 Text compression 3 2 Static Huffman coding 5 2.1 Encoding : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 5 2.2 Decoding : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 11 3 Dynamic Huffman coding 12 3.1 Encoding : : : : : : : ..."
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Cited by 1 (0 self)
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Contents 1 Text compression 3 2 Static Huffman coding 5 2.1 Encoding : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 5 2.2 Decoding : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 11 3 Dynamic Huffman coding 12 3.1 Encoding
Second Order Analysis of Data Compression Algorithms
"... In the first order analysis of a lossless data compression algorithm, one addresses the following question: For n consecutive data samples generated by a stationary source, is the difference between the expected codeword length and the entropy equal to o(n)? If the answer is yes, one can attempt a s ..."
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In the first order analysis of a lossless data compression algorithm, one addresses the following question: For n consecutive data samples generated by a stationary source, is the difference between the expected codeword length and the entropy equal to o(n)? If the answer is yes, one can attempt a
DIGITAL GENERIC DATA COMPRESSION ALGORITHMS USING MATLAB
"... Generic data compression algorithms is an area of digital processing that is focusing on reducing bit rate of the speech signal for transmission or storage without significant loss of quality. The focus of this paper is to compress the digital speech using wavelet transform. The main idea behind the ..."
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Generic data compression algorithms is an area of digital processing that is focusing on reducing bit rate of the speech signal for transmission or storage without significant loss of quality. The focus of this paper is to compress the digital speech using wavelet transform. The main idea behind
Evaluating GrammarBased Data Compression Algorithms
, 2001
"... The idea behind a grammar compressor is to represent a string by finding a small contextfree grammar that uniquely accepts it. This thesis is part of a sequence of works that explores how well a particular grammar compressor exploits the grammar model  that is, what is the ratio between the size ..."
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Cited by 1 (0 self)
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of a grammar produced by an algorithm and the smallest grammar for that particular input. Previous work on data compression algorithms focuses on analyzing how a compression algorithm performs when processing strings from stationary ergodic sources.
Lossless Data Compression Algorithm – A Review
"... Abstract — Data compression is more significant thing in recent world. Data compression is the science and skill of representing information in a compact form. Storage, transmission and processing of data are the integral part of information system. Enormous data demands additional resources. This l ..."
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. This leads to increase in hardware and transmission cost. Hence, resource optimization is the need of time. Instead of transmitting such data as it is, if we compress that data by applying some compression algorithm and to make sure that it will not hamper the quality of original data. Several lossless data
Results 1  10
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