Browsing Computer Science and Automation (CSA) by Title
Now showing items 226-245 of 394
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Loop Transformations for Multi-/Many-Core Architectures using Machine Learning
Loop transformation techniques such as loop tiling, loop interchange and unroll-and-jam help expose better coarse-grain and fine-grain data-level parallelisms as well as exploit data locality. These transformations are ... -
Low Power Test Methodology For SoCs : Solutions For Peak Power Minimization
(2013-09-13)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 Low-Complexity Algorithm For Intrusion Detection In A PIR-Based Wireless Sensor Network
(2011-08-25)This thesis investigates the problem of detecting an intruder in the presence of clutter in a Passive Infra-Red (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
(2017-12-05)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
(2018-01-30)We address the task of mapping a given domain model (e.g., an industry-standard 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 axis-parallel 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
(2009-07-08)A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities. In the presence of grid users who are autonomous, ... -
Mechanism Design For Strategic Crowdsourcing
(Indian Institute of Science, 2013-12-17)This thesis looks into the economics of crowdsourcing using game theoretic modeling. The art of aggregating information and expertise from a diverse population has been in practice since a long time. The Internet and the ... -
A Memory Allocation Framework for Optimizing Power Consumption and Controlling Fragmentation
(2018-07-20)Large physical memory modules are necessary to meet performance demands of today's ap- plications but can be a major bottleneck in terms of power consumption during idle periods or when systems are running with workloads ... -
MIST : Mlgrate The Storage Too
(2017-05-25)We address the problem of migration of local storage of desktop users to remote sites. Assuming a network connection is maintained between the source and destination after the migration makes it possible for us to transfer ... -
Mitigating Bias via Algorithms with Fairness Guarantees
The rapid integration of automated decision-making systems in critical domains such as resume screening, loan approval, content recommendation, and disaster containment has raised significant concerns regarding biases in ... -
An MLIR-Based High-Level Synthesis Compiler for Hardware Accelerator Design
The emergence of machine learning, image and audio processing on edge devices has motivated research towards power-efficient custom hardware accelerators. Though FPGAs are an ideal target for custom accelerators, the ... -
Model Checking Temporal Properties of Presburger Counter Systems
Counter systems are a well-known and powerful modeling notation for specifying infnite state systems. In this thesis we target the problem of checking temporal properties of counter systems. We address three predominant ... -
Model Extraction and Active Learning
Machine learning models are increasingly being offered as a service by big companies such as Google, Microsoft and Amazon. They use Machine Learning as a Service (MLaaS) to expose these machine learning models to the ... -
Model Extraction Defense using Modified Variational Autoencoder
Machine Learning as a Service (MLaaS) exposes machine learning (ML) models that are trained on confidential datasets to users in the form of an Application Programming Interface (API). Since the MLaaS models are deployed ... -
Model-based Safe Deep Reinforcement Learning and Empirical Analysis of Safety via Attribution
During initial iterations of training in most Reinforcement Learning (RL) algorithms, agents perform a significant number of random exploratory steps, which in the real-world limit the practicality of these algorithms ... -
Model-Checking in Presburger Counter Systems using Accelerations
(2018-04-18)Model checking is a powerful technique for analyzing reach ability and temporal properties of finite state systems. Model-checking finite state systems has been well-studied and there are well known efficient algorithms ... -
Model-Checking Infinite-State Systems For Information Flow Security Properties
(2017-02-16)Information flow properties are away of specifying security properties of systems ,dating back to the work of Goguen and Meseguer in the eighties. In this framework ,a system is modeled as having high-level (or confidential)events ... -
Modeling and Adaptive Scheduling Strategies for Distributed Graph Algorithms
Graph processing at scales of millions-billions of vertices and edges has become common to solve real-world problems in domains like social networks, smart cities and genomics. Distributed "Big Data" platforms for graph ...