Computer Science and Automation (CSA)
Recent Submissions

Robust Algorithms for recovering planted structures in Semirandom instances
In this thesis, we study algorithms for three fundamental graph problems. These are NPhard problems which have not been understood completely as there is a signifiicant gap between the algorithmic and the hardness fronts ... 
Signcryption in a Quantum World
With recent advancements and research on quantum computers, it is conjectured that in the foreseeable future, sufficiently large quantum computers will be built to break essentially all public key cryptosystems currently ... 
Honest Majority and Beyond: Efficient Secure Computation over Small Population
Secure MultiParty Computation for small population has witnessed notable practicallyefficient works in the setting of both honest majority and dishonest majority. While honest majority provides the promise of stronger ... 
Stochastic Approximation with Markov Noise: Analysis and applications in reinforcement learning
Stochastic approximation algorithms are sequential nonparametric methods for finding a zero or minimum of a function in the situation where only the noisy observations of the function values are available. Two timescale ... 
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 ... 
Practically Efficient Secure Small Party Computation over the Internet
Secure Multiparty Computation (MPC) with small population has drawn focus specifically due to customization in techniques and resulting efficiency that the constructions can offer. Practically efficient constructions ... 
Algorithms for Challenges to Practical Reinforcement Learning
Reinforcement learning (RL) in real world applications faces major hurdles  the foremost being safety of the physical system controlled by the learning agent and the varying environment conditions in which the autonomous ... 
Recommendations in Complex Networks: Unifying Structure into Random Walk
Making recommendations or predicting links which are likely to exist in the future is one of the central problems in network science and graph mining. In spite of modern stateof theart approaches for link prediction, ... 
Design of Trusted Market Platforms using Permissioned Blockchains and Game Theory
The blockchain concept forms the backbone of a new wave technology that promises to be deployed extensively in a wide variety of industrial and societal applications. Governments, financial institutions, banks, industrial ... 
Expanders in Arithmetic Circuit Lower Bound : Towards a Separation Between ROABPs and Multilinear Depth 3 Circuits
Consider the problem of Polynomial Identity Testing(PIT): we are given an arithmetic circuit computing a multivariate polynomial over some eld and we have to determine whether that polynomial is identically zero or not. ... 
On the Round Complexity Landscape of Secure Multiparty Computation
In secure multiparty computation (MPC), n parties wish to jointly perform a computation on their private inputs in a secure way, so that no adversary corrupting a subset of the parties can learn more information than their ... 
Hypergraph Network Models: Learning, Prediction, and Representation in the Presence of HigherOrder Relations
The very thought about “relating” objects makes us assume the relation would be “pairwise”, and not of a “higherorder” — involving possibly more than two of them at a time. Yet in reality, higherorder relations do exist ... 
Towards Secure and Efficient Realization of PairingBased Signatures from Static Assumptions.
Bilinear pairing defined over elliptic curve group was first used to design novel cryptosystem in 2000. Since then a large number of cryptosystems has been proposed in pairingbased cryptography (PBC). The main tool for ... 
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 ... 
Efficient and Secure Search over Encrypted Data
Due to a variety of crucial bene fits, enterprises outsource their data to cloud resident storage. The outsourced data needs to be stored in encrypted form on remote untrusted servers to preserve privacy. However, if the ... 
Program Analyses to Support Memorysaving Refactorings in Java Programs
Software commonly consumes unexpectedly high amounts of memory, frequently due to programming idioms that are used to make software more reliable, maintainable and understandable. In the case of modern objectoriented ... 
Representing Networks: Centrality, Node Embeddings, Community Outliers and Graph Representation
Networks are ubiquitous. We start our technical work in this thesis by exploring the classical concept of node centrality (also known as influence measure) in information networks. Like clustering, node centrality is also ... 
Algorithms for Stochastic Optimization, Statistical Estimation and Markov Decision Processes
Stochastic approximation deals with the problem of finding zeros of a function expressed as an expectation of a random variable. In this thesis we propose convergent algorithms for problems in optimization, statistical ... 
Embedding Networks: Node and Graph Level Representations
Graph neural networks gained significant attention for graph representation and classification in the machine learning community. For graph classification, different pooling techniques are introduced, but none of them has ... 
Decision Making under Uncertainty : Reinforcement Learning Algorithms and Applications in Cloud Computing, Crowdsourcing and Predictive Analytics
In this thesis, we study both theoretical and practical aspects of decision making, with a focus on reinforcement learning based methods. Reinforcement learning (RL) is a form of semisupervised learning in which the agent ...