Browsing Computer Science and Automation (CSA) by Title
Now showing items 203-222 of 362
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Learning Robust Support Vector Machine Classifiers With Uncertain Observations
(2015-08-19)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 Preference-based Multi-Armed 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
(2017-12-07)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 Non-malleable Secret Sharing
Non-malleable 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
(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 ... -
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 ... -
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 ...