Results 1 - 10 of 14,079

Gradient-based learning applied to document recognition

by Yann Lecun, Léon Bottou, Yoshua Bengio, Patrick Haffner - Proceedings of the IEEE , 1998
"... Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradientbased learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify hi ..."
Abstract - Cited by 1533 (84 self) - Add to MetaCart
to deal with the variability of two dimensional (2-D) shapes, are shown to outperform all other techniques. Real-life document recognition systems are composed of multiple modules including field extraction, segmentation, recognition, and language modeling. A new learning paradigm, called graph

Formal Ontology and Information Systems

by Nicola Guarino , 1998
"... Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We sh ..."
Abstract - Cited by 897 (11 self) - Add to MetaCart
Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We

From Data Mining to Knowledge Discovery in Databases.

by Usama Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth - AI Magazine, , 1996
"... ■ Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery in database ..."
Abstract - Cited by 538 (0 self) - Add to MetaCart
research directions in the field. A cross a wide variety of fields, data are being collected and accumulated at a dramatic pace. There is an urgent need for a new generation of computational theories and tools to assist humans in extracting useful information (knowledge) from the rapidly growing volumes

The Nanoparticle Field Extraction Thruster

by Louis Musinski , Thomas Liu , Inkyu Eu , Brian Gilchrist , Alec Gallimore , Joanna Mirecki-Millunchick , David Morris - NanoFET,” JANNAF 3rd Spacecraft Propulsion Subcommittee Meeting , 2008
"... Abstract This paper introduces a nanoparticle field extraction thruster (nanoFET) concept that does not depend on the liquid delivery of micro and nano-particles for extraction and acceleration. The no-liquid approach potentially provides important advantages such as allowing the use of smaller par ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Abstract This paper introduces a nanoparticle field extraction thruster (nanoFET) concept that does not depend on the liquid delivery of micro and nano-particles for extraction and acceleration. The no-liquid approach potentially provides important advantages such as allowing the use of smaller

Statistical pattern recognition: A review

by Anil K. Jain, Robert P. W. Duin, Jianchang Mao - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2000
"... The primary goal of pattern recognition is supervised or unsupervised classification. Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, neural network techniques ..."
Abstract - Cited by 1035 (30 self) - Add to MetaCart
techniques and methods imported from statistical learning theory have bean receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection

Theory of Elasticity,

by S P Timoshenko , J N Goodier , 1951
"... ABSTRACT The knowledge of the in-situ stress field in rock masses is in general of crucial importance in various areas of geo-engineering, such as mining or civil underground excavations, hydrocarbon extraction, CO2 storage, hydraulic fracture operations, etc. In the context of the Finite Element ..."
Abstract - Cited by 710 (1 self) - Add to MetaCart
ABSTRACT The knowledge of the in-situ stress field in rock masses is in general of crucial importance in various areas of geo-engineering, such as mining or civil underground excavations, hydrocarbon extraction, CO2 storage, hydraulic fracture operations, etc. In the context of the Finite Element

K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation

by Michal Aharon, et al. , 2006
"... In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many and inc ..."
Abstract - Cited by 935 (41 self) - Add to MetaCart
and include compression, regularization in inverse problems, feature extraction, and more. Recent activity in this field has concentrated mainly on the study of pursuit algorithms that decompose signals with respect to a given dictionary. Designing dictionaries to better fit the above model can be done

Data Mining: Concepts and Techniques

by Jiawei Han, Micheline Kamber , 2000
"... Our capabilities of both generating and collecting data have been increasing rapidly in the last several decades. Contributing factors include the widespread use of bar codes for most commercial products, the computerization of many business, scientific and government transactions and managements, a ..."
Abstract - Cited by 3142 (23 self) - Add to MetaCart
, a promising and flourishing frontier in database systems and new database applications. Data mining, also popularly referred to as knowledge discovery in databases (KDD), is the automated or convenient extraction of patterns representing knowledge implicitly stored in large databases, data

Bursty and Hierarchical Structure in Streams

by Jon Kleinberg , 2002
"... A fundamental problem in text data mining is to extract meaningful structure from document streams that arrive continuously over time. E-mail and news articles are two natural examples of such streams, each characterized by topics that appear, grow in intensity for a period of time, and then fade aw ..."
Abstract - Cited by 394 (2 self) - Add to MetaCart
A fundamental problem in text data mining is to extract meaningful structure from document streams that arrive continuously over time. E-mail and news articles are two natural examples of such streams, each characterized by topics that appear, grow in intensity for a period of time, and then fade

Renormalization in quantum field theory and the Riemann-Hilbert problem. II. The β-function, diffeomorphisms and the renormalization group

by Alain Connes, Dirk Kreimer - Comm. Math. Phys
"... We show that renormalization in quantum field theory is a special instance of a general mathematical procedure of multiplicative extraction of finite values based on the Riemann–Hilbert problem. Given a loop γ(z), |z | = 1 of elements of a complex Lie group G the general procedure is given by evalu ..."
Abstract - Cited by 332 (39 self) - Add to MetaCart
We show that renormalization in quantum field theory is a special instance of a general mathematical procedure of multiplicative extraction of finite values based on the Riemann–Hilbert problem. Given a loop γ(z), |z | = 1 of elements of a complex Lie group G the general procedure is given
Results 1 - 10 of 14,079