Browsing Computer Science and Automation (CSA) by Advisor "Narasimha Murty, M"
Now showing items 1-15 of 15
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ACE-Model: A Conceptual Evolutionary Model For Evolutionary Computation And Artificial Life
(Indian Institute of Science, 2005-02-07)Darwinian Evolutionary system - a system satisfying the abstract conditions: reproduction with heritable variation, in a finite world, giving rise to Natural Selection encompasses a complex and subtle system of interrelated ... -
Efficient Frequent Closed Itemset Algorithms With Applications To Stream Mining And Classification
(2010-08-24)Data mining is an area to find valid, novel, potentially useful, and ultimately understandable abstractions in a data. Frequent itemset mining is one of the important data mining approaches to find those abstractions in ... -
Efficient Kernel Methods For Large Scale Classification
(2011-02-22)Classification algorithms have been widely used in many application domains. Most of these domains deal with massive collection of data and hence demand classification algorithms that scale well with the size of the data ... -
Embedding Networks: Node and Graph Level Representations
Graph neural networks gained significant attention for graph representation and classification in the machine learning community. For graph classification, different pooling techniques are introduced, but none of them has ... -
Hierarchical Data Structures for Pattern Recognition
(Indian Institute of Science, 2005-02-22)Pattern recognition is an important area with potential applications in computer vision, Speech understanding, knowledge engineering, bio-medical data classification, earth sciences, life sciences, economics, psychology, ... -
Kernel Methods Fast Algorithms and real life applications
(Indian Institute of Science, 2005-02-08)Support Vector Machines (SVM) have recently gained prominence in the field of machine learning and pattern classification (Vapnik, 1995, Herbrich, 2002, Scholkopf and Smola, 2002). Classification is achieved by finding a ... -
Large Data Clustering And Classification Schemes For Data Mining
(2009-03-20)Data Mining deals with extracting valid, novel, easily understood by humans, potentially useful and general abstractions from large data. A data is large when number of patterns, number of features per pattern or both are ... -
On Generalized Measures Of Information With Maximum And Minimum Entropy Prescriptions
(2008-01-29)Kullback-Leibler relative-entropy or KL-entropy of P with respect to R defined as ∫xlnddPRdP , where P and R are probability measures on a measurable space (X, ), plays a basic role in the definitions of classical information ... -
Outlier Detection with Applications in Graph Data Mining
(2018-04-24)Outlier detection is an important data mining task due to its applicability in many contemporary applications such as fraud detection and anomaly detection in networks, etc. It assumes significance due to the general ... -
Recommendations in Complex Networks: Unifying Structure into Random Walk
Making recommendations or predicting links which are likely to exist in the future is one of the central problems in network science and graph mining. In spite of modern state-of- the-art approaches for link prediction, ... -
Semantic Analysis of Web Pages for Task-based Personal Web Interactions
(2017-11-27)Mobile widgets now form a new paradigm of simplified web. Probably, the best experience of the Web is when a user has a widget for every frequently executed task, and can execute it anytime, anywhere on any device. However, ... -
Sentiment-Driven Topic Analysis Of Song Lyrics
(2015-08-17)Sentiment Analysis is an area of Computer Science that deals with the impact a document makes on a user. The very field is further sub-divided into Opinion Mining and Emotion Analysis, the latter of which is the basis for ...