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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 ...
Quantum-Safe Identity-Based Signature Scheme in Multivariate Quadratic Setting
Cryptographic techniques are essential for the security of communication in modern society. Today, nearly all public key cryptographic schemes used in practice are based on the two problems of factoring large integers and ...
Enhancing Coverage and Robustness of Database Generators
Generating synthetic databases that capture essential data characteristics of client databases is a common requirement for enterprise database vendors. This need stems from a variety of use-cases, such as application testing ...
A Syntactic Neural Model For Question Decomposition
Question decomposition along with single-hop Question Answering (QA) system serve as useful modules in developing multi-hop Question Answering systems, mainly because the resulting QA system is interpretable and has been ...
Learning Invariants for Verification of Programs and Control Systems
Deductive verification techniques in the style of Floyd and Hoare have the potential to give us concise, compositional, and scalable proofs of the correctness of various kinds of software systems like programs and control ...
On Learning and Lower Bound Problems Related to the Iterated Matrix Multiplication Polynomial
The iterated matrix multiplication polynomial (IMM) of width w and length d is the 1x1 entry in the product of d square matrices of size w. The w^2d entries in the d matrices are distinct variables. In this thesis, we study ...
Algorithms for Fair Decision Making: Provable Guarantees and Applications
The topic of fair allocation of indivisible items has received significant attention because of its applicability in several real-world settings. This has led to a vast body of work focusing on defining appropriate fairness ...
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 ...