Browsing Computer Science and Automation (CSA) by Title
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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 ... 
Matching Domain Model with Source Code using Relationships
(20180130)We address the task of mapping a given domain model (e.g., an industrystandard reference model) for a given domain (e.g., ERP), with the source code of an independently developed application in the same domain. This has ... 
Maximum Independent Set of Rectangles  An Empirical Study
We study the Maximum Independent Set of Rectangles (MISR) problem. The problem involves a collection of n axisparallel rectangles in 2D with weights. For the unweighted case, the goal is to find the maximum number of ... 
Mean Field Based Investigations for Inducing Socially Optimal Epidemic Behavior in Rational Individuals
In the recent years, the world has been devastated by multiple pandemics arising out of different variants of the Corona virus. When an epidemic or pandemic strikes, it is important to move quickly to contain and suppress ... 
A Mechanism Design Approach To Resource Procurement In Computational Grids With Rational Resource Providers
(20090708)A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to highend computational capabilities. In the presence of grid users who are autonomous, ...