Browsing Computer Science and Automation (CSA) by Title
Now showing items 201220 of 380

Kernel Methods Fast Algorithms and real life applications
(Indian Institute of Science, 20050208)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 ... 
A KnowledgeBased Approach To Pattern Clustering
(Indian Institute of Science, 20050311)The primary objective of this thesis is to develop a methodology for clustering of objects based on their functionality typified by the notion of concept. We begin by giving a formal definition of concept. By assigning a ... 
Language Support for Exploiting Software Structure Specifications
(Indian Institute of Science, 20050216)Precise specification of the architecture and design of software is a good practice. Such specifications contain a lot of information about the software that can potentially be exploited by tools, to reduce redundancy ... 
Language Support For Testing CORBA Based Applications
(Indian Institute of Science, 20051207)Component Based Development has emerged as economical, reusable, scalable way of developing enterprise as well as embedded software applications. Testing distributed component based systems is difficult when third party ... 
Large Data Clustering And Classification Schemes For Data Mining
(20090320)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 ... 
Large Scale Graph Processing in a Distributed Environment
(20180525)Graph algorithms are ubiquitously used across domains. They exhibit parallelism, which can be exploited on parallel architectures, such as multicore processors and accelerators. However, real world graphs are massive in ... 
Large Scale Implementation Of The Block Lanczos Algorithm
(20100816)Large sparse matrices arise in many applications, especially in the major problems of Cryptography of factoring integers and computing discrete logarithms. We focus attention on such matrices called sieve matrices generated ... 
Learning Algorithms Using ChanceConstrained Programs
(20100708)This thesis explores ChanceConstrained Programming (CCP) in the context of learning. It is shown that chanceconstraint approaches lead to improved algorithms for three important learning problems — classification with ... 
Learning Decentralized GoalBased Vector Quantization
(20120504) 
Learning Dynamic Prices In Electronic Markets
(20110419) 
Learning Invariants for Verification of Programs and Control Systems
Deductive verification techniques in the style of Floyd and Hoare have the potential to give us concise, compositional, and scalable proofs of the correctness of various kinds of software systems like programs and control ... 
Learning Robust Support Vector Machine Classifiers With Uncertain Observations
(20150819)The central theme of the thesis is to study linear and non linear SVM formulations in the presence of uncertain observations. The main contribution of this thesis is to derive robust classfiers from partial knowledge of ... 
Learning to Adapt Policies for uSD card
Machine Learning(ML) for Systems is a new and promising research area where performance of computer systems is optimized using machine learning methods. ML for Systems has outperformed traditional heuristics methods in ... 
Learning Tournament Solutions from Preferencebased MultiArmed Bandits
We consider the dueling bandits problem, a sequential decision task where the goal is to learn to pick `good' arms out of an available pool by actively querying for and observing relative preferences between selected pairs ... 
Learning with Complex Performance Measures : Theory, Algorithms and Applications
(20171207)We consider supervised learning problems, where one is given objects with labels, and the goal is to learn a model that can make accurate predictions on new objects. These problems abound in applications, ranging from ... 
Locally Reconstructable Nonmalleable Secret Sharing
Nonmalleable secret sharing (NMSS) schemes, introduced by Goyal and Kumar (STOC 2018), ensure that a secret m can be distributed into shares m1,...,mn (for some n), such that any t (a parameter <= n) shares can be ... 
Low Power Test Methodology For SoCs : Solutions For Peak Power Minimization
(20130913)Power dissipated during scan testing is becoming increasingly important for today’s very complex sequential circuits. It is shown that the power dissipated during test mode operation is in general higher than the power ... 
A LowComplexity Algorithm For Intrusion Detection In A PIRBased Wireless Sensor Network
(20110825)This thesis investigates the problem of detecting an intruder in the presence of clutter in a Passive InfraRed (PIR) based Wireless Sensor Network (WSN). As one of the major objectives in a WSN is to maximize battery life, ... 
Machine Learning and Rank Aggregation Methods for Gene Prioritization from Heterogeneous Data Sources
(20171205)Gene prioritization involves ranking genes by possible relevance to a disease of interest. This is important in order to narrow down the set of genes to be investigated biologically, and over the years, several computational ...