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180
A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach
- J MOL BIOL
, 2001
"... We have introduced a new method of protein secondary structure prediction which is based on the theory of support vector machine (SVM). SVM represents a new approach to supervised pattern classification which has been successfully applied to a wide range of pattern recognition problems, including ob ..."
Abstract
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Cited by 177 (3 self)
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comparable to existing single prediction methods. Furthermore a useful "reliability index" for the predictions was developed. In addition, SVM has many attractive features, including effective avoidance of overfitting, the ability to handle large feature spaces, information condensing of the given
Semantic Indexing of Multimedia Content Using Visual, Audio, and Text Cues
- EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING 2003:2, 170–185
, 2003
"... We present a learning-based approach to the semantic indexing of multimedia content using cues derived from audio, visual, and text features. We approach the problem by developing a set of statistical models for a predefined lexicon. Novel concepts are then mapped in terms of the concepts in the lex ..."
Abstract
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Cited by 53 (2 self)
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We present a learning-based approach to the semantic indexing of multimedia content using cues derived from audio, visual, and text features. We approach the problem by developing a set of statistical models for a predefined lexicon. Novel concepts are then mapped in terms of the concepts
A Novel Approach for Password Strength Analysis through Support Vector Machine
"... Abstract — Passwords are ubiquitous authentication methods and they represent the identity of an individual for a system. Users are consistently told that a strong password is essential these days to protect private data. Despite the existence of more secure methods of authenticating users, includin ..."
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vulnerabilities are not exploited. This work employs machine Learning technique to analyze the strength of the password to facilitate organizations launch a multifaceted defense against password breach and provide a highly secure environment. A supervised learning algorithm namely Support Vector Machine is used
Locally Linear Discriminant Analysis for Multimodally Distributed Classes for Face Recognition with a Single Model Image
- IEEE Trans. Pattern Analysis and Machine Intelligence
, 2005
"... Abstract—We present a novel method of nonlinear discriminant analysis involving a set of locally linear transformations called “Locally Linear Discriminant Analysis (LLDA). ” The underlying idea is that global nonlinear data structures are locally linear and local structures can be linearly aligned. ..."
Abstract
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Cited by 78 (5 self)
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of the solution. A novel gradient-based learning algorithm is proposed for finding the optimal set of local linear bases. The optimization does not exhibit a local-maxima problem. The transformation functions facilitate robust face recognition in a low-dimensional subspace, under pose variations, using a single
port Vector Machines, Kernel Fisher Discriminant analysis
"... Abstract | This review provides an introduction to Sup- ..."
Based on Support Vector Machines
, 2003
"... The support vector machine, as a novel type of learning machine, for the first time, was used to develop a QSAR model of 57 analogues of ethyl 2-[(3-methyl-2,5-dioxo(3-pyrrolinyl))amino]-4-(trifluoromethyl)pyrimidine-5-carboxylate (EPC), an inhibitor of AP-1 and NF-κB mediated gene expression, based ..."
Abstract
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The support vector machine, as a novel type of learning machine, for the first time, was used to develop a QSAR model of 57 analogues of ethyl 2-[(3-methyl-2,5-dioxo(3-pyrrolinyl))amino]-4-(trifluoromethyl)pyrimidine-5-carboxylate (EPC), an inhibitor of AP-1 and NF-κB mediated gene expression
Ensemble-based discriminant learning with boosting for face recognition
- 10, 2009 DRAFT IVP/713183.V2 23
, 2006
"... Abstract—In this paper, we propose a novel ensemble-based approach to boost performance of traditional Linear Discriminant Analysis (LDA)-based methods used in face recognition. The ensemble-based approach is based on the recently emerged technique known as “boosting. ” However, it is generally beli ..."
Abstract
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Cited by 32 (6 self)
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believed that boosting-like learning rules are not suited to a strong and stable learner such as LDA. To break the limitation, a novel weakness analysis theory is developed here. The theory attempts to boost a strong learner by increasing the diversity between the classifiers created by the learner
Connecting Human and Machine Learning via Probabilistic Models of Cognition
- In: Technical Program. 10th Annual Conference of the International Speech Communication Association
, 2009
"... Human performance defines the standard that machine learning systems aspire to in many areas, including learning language. This suggests that studying human cognition may be a good way to develop better learning algorithms, as well as providing basic insights into how the human mind works. However, ..."
Abstract
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Cited by 1 (0 self)
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Human performance defines the standard that machine learning systems aspire to in many areas, including learning language. This suggests that studying human cognition may be a good way to develop better learning algorithms, as well as providing basic insights into how the human mind works. However
Support Vector Machines under Adversarial Label Contamination
"... Machine learning algorithms are increasingly being applied in security-related tasks such as spam and malware detection, although their security properties against deliberate attacks have not yet been widely understood. Intelligent and adaptive attackers may indeed exploit specific vulnerabilities e ..."
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Machine learning algorithms are increasingly being applied in security-related tasks such as spam and malware detection, although their security properties against deliberate attacks have not yet been widely understood. Intelligent and adaptive attackers may indeed exploit specific vulnerabilities
Learning to Annotate Scientific Publications
"... Annotating scientific publications with keywords and phrases is of great importance to searching, indexing, and cataloging such documents. Unlike previous studies that focused on usercentric annotation, this paper presents our investigation of various annotation characteristics on service-centric an ..."
Abstract
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Cited by 3 (1 self)
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-centric annotation. Using a large number of publicly available annotated scientific publications, we characterized and compared the two different types of annotation processes. Furthermore, we developed an automatic approach of annotating scientific publications based on a machine learning algorithm and a set
Results 1 - 10
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180
