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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 ...
Hypergraph Network Models: Learning, Prediction, and Representation in the Presence of Higher-Order Relations
The very thought about “relating” objects makes us assume the relation would be “pairwise”, and
not of a “higher-order” — involving possibly more than two of them at a time. Yet in reality,
higher-order relations do exist ...
Constant-rate Non-malleable Codes and their Applications
Non-malleable codes(NMC) introduced by Dziembowski, Pietrzak and Wichs in ITCS 2010,
provide powerful security guarantees where error-correcting codes can not provide any guarantee: a decoding of tampered codeword is ...
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 ...
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 ...
FA RCU: Fault Aware Read-Copy-Update
Deferred freeing is the fundamental technique used in Read-Copy-Update (RCU) synchronization technique where reclamation of resources is deferred until the completion of all active RCU read-side critical sections. We observe ...
Novel Reinforcement Learning Algorithms and Applications to Hybrid Control Design Problems
The thesis is a compilation of two independent works.
In the first work, we develop novel weight assignment procedure, which helps us develop several schedule based algorithms. Learning the value function of a given policy ...
Towards Effcient Privacy-Preserving Two-Party k-Means Clustering Protocol
Two-party data mining is a win-win game if played with a guarantee of data privacy from each other.
This guarantee is provided by the use of cryptographic techniques in designing the two-party protocol.
The need to ...
IO Pattern Aware Methods to Improve the Performance and Lifetime of NAND SSD
Modern SSDs can store multiple bits per transistor which enables it to have higher
storage capacities. Low cost per bit of such SSDs has made it a commercial success. As
of 2018, cells with an ability to store three bits ...
Algorithms for Multilingual IR in Low Resource Languages using Weakly Aligned Corpora
Multilingual information retrieval (MLIR) methods generally rely on linguistic resources such
as dictionaries, parallel corpora, etc., to overcome the language barrier. For low resource
languages without these resources, ...