Browsing Computer Science and Automation (CSA) by Title
Now showing items 225-244 of 377
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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 ... -
Modeling and verification of database-accessing applications
Databases are central to the functioning of most IT-enabled processes and services. In many domains, databases are accessed and updated via applications written in general-purpose lan- guages, as such applications need ... -
Module Grobner Bases Over Fields With Valuation
(2017-07-12)Tropical geometry is an area of mathematics that interfaces algebraic geometry and combinatorics. The main object of study in tropical geometry is the tropical variety, which is the combinatorial counterpart of a classical ... -
Morse-Smale Complexes : Computation and Applications
(2018-01-30)In recent decades, scientific data has become available in increasing sizes and precision. Therefore techniques to analyze and summarize the ever increasing datasets are of vital importance. A common form of scientific ... -
MPCLeague: Robust MPC Platform for Privacy-Preserving Machine Learning
In the modern era of computing, machine learning tools have demonstrated their potential in vital sectors, such as healthcare and finance, to derive proper inferences. The sensitive and confidential nature of the data in ... -
Multi-Armed Bandits – On Range Searching and On Slowly-varying Non-stationarity
Multi-Armed Bandits (MAB) is a popular framework for modelling sequential decision-making problems under uncertainty. This thesis is a compilation of two independent works on MABs. 1. In the first work, we study a ... -
Multi-label Classification with Multiple Label Correlation Orders And Structures
(2018-06-18)Multilabel classification has attracted much interest in recent times due to the wide applicability of the problem and the challenges involved in learning a classifier for multilabeled data. A crucial aspect of multilabel ... -
Multimodal Deep Learning for Multi-Label Classification and Ranking Problems
(2018-06-11)In recent years, deep neural network models have shown to outperform many state of the art algorithms. The reason for this is, unsupervised pretraining with multi-layered deep neural networks have shown to learn better ... -
A Nash Bargaining Based Bid Optimizer for Sponsored Search Auctions
The on-line advertising market involving displaying of Ads against search results by a search engine is growing at a fast rate. A majority of the search engine companies sell their advertising space through auctions which ... -
Near-Duplicate Detection Using Instance Level Constraints
(2011-08-09)For the task of near-duplicate document detection, comparison approaches based on bag-of-words used in information retrieval community are not sufficiently accurate. This work presents novel approach when instance-level ... -
Network Centrality Measures And Their Applications
(2014-03-03)Study of complex networks by researchers from many disciplines has provided penetrating insights on various complex systems. A study of the world wide web from a network theoretic perspective has led to the design of new ...