Browsing Computer Science and Automation (CSA) by thesis submitted date"2025"
Now showing items 1-20 of 20
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Algorithms for various cost criteria in Reinforcement Learning
In this thesis we will look at various Reinforcement Learning algorithms. We will look at algorithms for various cost criteria or reward objectives namely Finite Horizon, Discounted Cost, Risk-Sensitive Cost. For Finite ... -
CHARGE: Accelerating GNN Training via CPU Sampling in Heterogeneous CPU–GPU Environment
Graph Neural Networks (GNNs) have demonstrated exceptional performance across a wide range of applications, driving their widespread adoption. Current frameworks employ CPU and GPU resources—either in isolation or ... -
Combinatorial Problems arising in Quantum Physics and Model counting
This thesis investigates some combinatorial problems arising in quantum physics and model counting. In particular, we develop new graph-theoretic techniques to resolve some open questions from quantum photonics. We also ... -
Controller Synthesis Techniques for Infinite-State Reactive Systems
Reactive systems are ubiquitous, with various use cases ranging from controllers for cyber-physical systems to programs that run on multipurpose computers. A system is reactive if it continually behaves in a specific manner ... -
Design of AI-based Computational Framework for Accurate Detection of Polycystic Ovarian Disease and Ovarian Cancer Using Ultrasound, CT and Histopathology Images
Polycystic Ovarian Disease (PCOD) and Ovarian Cancer (OC) represent critical health challenges affecting millions of women globally. Early and accurate detection of these conditions is essential for effective clinical ... -
Enhancing Privacy and Efficiency of Distributed Encryption
The primary objective of a distributed system is to eliminate reliance on a central authority. In a distributed encryption scheme, users should be able to generate their key materials independently while securely sharing ... -
Feature Tracking and Visual Analysis of Temporal Scalar Fields in the Ocean
The Bay of Bengal (BoB) has maintained its salinity distribution over the years despite a continuous flow of fresh water entering it through rivers on the northern coast, which can dilute its salinity. This can be ... -
A framework for timing analysis of event-driven applications
Event-driven applications, particularly those based on the publish–subscribe communication model are widely adopted to build responsive and decoupled applications in domains such as robotics, the Internet of Things ... -
IEDFuRL: A Black-box Fuzz Tester for IEC61850-based Intelligent Electronic Devices using Reinforcement Learning
Intelligent Electronic Devices (IEDs) are essential components of modern power grids, functioning as microprocessor-based controllers that facilitate communication, monitoring, protection, and control within Supervisory ... -
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 ... -
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 ... -
Multi-timescale and Multi-agent Reinforcement Learning Algorithms
This thesis presents six novel works involving several research domains, such as reinforcement learning (RL)– both with or without function approximators including deep neural networks, multi-agent RL, stochastic optimization, ... -
On Orbits and Border of Constant Read Circuits and Lower Bounds for Constant Depth Circuits
Two of the most common ways in which arithmetic circuits can be restricted is by requiring that they be constant read or constant depth. Constant depth circuits have received a lot of attention in the arithmetic circuit ... -
Protecting Deep Learning Models on Cloud Platforms with Trusted Execution Environments
Deep learning is rapidly integrated into different applications, from medical imaging to financial products. Organisations are spending enormous financial resources to train deep learning models. Often, many organisations ... -
PyGraph: Compiler Support for Efficient and Transparent Use of CUDA Graphs
CUDA Graphs --- a recent hardware feature introduced for NVIDIA GPUs --- aim to reduce CPU launch overhead by capturing and launching a series of GPU tasks (kernels) as a DAG. However, deploying CUDA Graphs faces several ... -
Secure Auctions with Rational Parties
Sealed bid auctions are used to allocate a resource among a set of interested parties. Traditionally, auctions need the presence of a trusted auctioneer to whom the bidders provide their private bid values. Existence of ... -
Secure Vickrey Auctions with Rational Parties
In this work, we construct a second price (Vickrey) auction protocol (SPA), which does not require any auctioneers and ensures total privacy in the presence of rational parties participating in the auction. In particular, ... -
Sequential Decision Making with Risk, Offline Data and External Influence: Bandits and Reinforcement Learning
Reinforcement Learning (RL) serves as a foundational framework for addressing sequential decision-making problems under uncertainty. In recent years, extensive research in this domain has led to significant advancements ... -
Studies in Probabilistic Model-Building Evolutionary Algorithms
Evolutionary algorithms (EAs) are a family of metaheuristics inspired by Darwin's theory of evolution through natural selection. They maintain and evolve a population of candidate solutions through stochastic variation and ... -
Zero Knowledge Proofs: Succinct Verification, Distributed Proofs and Lookup Arguments
Zero-Knowledge Proofs (ZKPs) are fundamental cryptographic tools enabling a prover to convince a verifier about the knowledge of a secret witness related to a public statement, without revealing any information beyond the ...