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The Nature of Statistical Learning Theory

by Vladimir N. Vapnik , 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 ..."
Abstract - Cited by 13236 (32 self) - Add to MetaCart
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

The University of Florida sparse matrix collection

by Timothy A. Davis - NA DIGEST , 1997
"... The University of Florida Sparse Matrix Collection is a large, widely available, and actively growing set of sparse matrices that arise in real applications. Its matrices cover a wide spectrum of problem domains, both those arising from problems with underlying 2D or 3D geometry (structural enginee ..."
Abstract - Cited by 536 (17 self) - Add to MetaCart
and graphs, economic and financial modeling, theoretical and quantum chemistry, chemical process simulation, mathematics and statistics, and power networks). The collection meets a vital need that artificially-generated matrices cannot meet, and is widely used by the sparse matrix algorithms community

Europarl: A Parallel Corpus for Statistical Machine Translation

by Philipp Koehn
"... We collected a corpus of parallel text in 11 languages from the proceedings of the European Parliament, which are published on the web 1. This corpus has found widespread use in the NLP community. Here, we focus on its acquisition and its application as training data for statistical machine translat ..."
Abstract - Cited by 519 (1 self) - Add to MetaCart
We collected a corpus of parallel text in 11 languages from the proceedings of the European Parliament, which are published on the web 1. This corpus has found widespread use in the NLP community. Here, we focus on its acquisition and its application as training data for statistical machine

A statistical interpretation of term specificity and its application in retrieval

by Karen Spärck Jones - Journal of Documentation , 1972
"... Abstract: The exhaustivity of document descriptions and the specificity of index terms are usually regarded as independent. It is suggested that specificity should be interpreted statistically, as a function of term use rather than of term meaning. The effects on retrieval of variations in term spec ..."
Abstract - Cited by 589 (3 self) - Add to MetaCart
Abstract: The exhaustivity of document descriptions and the specificity of index terms are usually regarded as independent. It is suggested that specificity should be interpreted statistically, as a function of term use rather than of term meaning. The effects on retrieval of variations in term

A Language Modeling Approach to Information Retrieval

by Jay M. Ponte, W. Bruce Croft , 1998
"... Models of document indexing and document retrieval have been extensively studied. The integration of these two classes of models has been the goal of several researchers but it is a very difficult problem. We argue that much of the reason for this is the lack of an adequate indexing model. This sugg ..."
Abstract - Cited by 1154 (42 self) - Add to MetaCart
an approach to retrieval based on probabilistic language modeling. We estimate models for each document individually. Our approach to modeling is non-parametric and integrates document indexing and document retrieval into a single model. One advantage of our approach is that collection statistics which

Collecting Statistics over Runtime Executions

by Bernd Finkbeiner, Sriram Sankaranarayanan, Henny B. Sipma - In Proceedings of Runtime Verification (RV’02) [1 , 2002
"... Abstract. We present an extension to linear-time temporal logic (LTL) that combines the temporal specification with the collection of statistical data. By collecting statistics over runtime executions of a program we can answer complex queries, such as “what is the average number of packet transmiss ..."
Abstract - Cited by 27 (1 self) - Add to MetaCart
Abstract. We present an extension to linear-time temporal logic (LTL) that combines the temporal specification with the collection of statistical data. By collecting statistics over runtime executions of a program we can answer complex queries, such as “what is the average number of packet

SRILM -- An extensible language modeling toolkit

by Andreas Stolcke - IN PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING (ICSLP 2002 , 2002
"... SRILM is a collection of C++ libraries, executable programs, and helper scripts designed to allow both production of and experimentation with statistical language models for speech recognition and other applications. SRILM is freely available for noncommercial purposes. The toolkit supports creation ..."
Abstract - Cited by 1218 (21 self) - Add to MetaCart
SRILM is a collection of C++ libraries, executable programs, and helper scripts designed to allow both production of and experimentation with statistical language models for speech recognition and other applications. SRILM is freely available for noncommercial purposes. The toolkit supports

Automatic Musical Genre Classification Of Audio Signals

by George Tzanetakis, Georg Essl, Perry Cook - IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING , 2002
"... ... describe music. They are commonly used to structure the increasing amounts of music available in digital form on the Web and are important for music information retrieval. Genre categorization for audio has traditionally been performed manually. A particular musical genre is characterized by sta ..."
Abstract - Cited by 829 (35 self) - Add to MetaCart
set of features for representing rhythmic structure and strength is proposed. The performance of those feature sets has been evaluated by training statistical pattern recognition classifiers using real world audio collections. Based on the automatic hierarchical genre classification two graphical user

On the Self-similar Nature of Ethernet Traffic (Extended Version)

by Will E. Leland, Murad S. Taqqu, Walter Willinger, Daniel V. Wilson , 1994
"... We demonstrate that Ethernet LAN traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal-like behavior, that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks, and that aggrega ..."
Abstract - Cited by 2213 (46 self) - Add to MetaCart
, and that aggregating streams of such traffic typically intensifies the self-similarity (“burstiness”) instead of smoothing it. Our conclusions are supported by a rigorous statistical analysis of hundreds of millions of high quality Ethernet traffic measurements collected between 1989 and 1992, coupled with a

Probabilistic Latent Semantic Indexing

by Thomas Hofmann , 1999
"... Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized ..."
Abstract - Cited by 1225 (10 self) - Add to MetaCart
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized
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