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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 ...
Robust Non-convex Penalties for Solving Sparse Linear Inverse Problems and Applications to Computational Imaging
Sparse linear inverse problems require the solution to the l-0-regularized least-squares cost, which is not computationally tractable. Approximate and computationally tractable solutions are obtained by employing ...
Protection Schemes for Maintaining the Coordination Time Interval Between the Relays in Micro-grid
Conventional power system alone cannot meet the ever growing needs of electrical power
in the world in a reliable manner. Under these circumstances, large penetration of Dis-
tributed generators in the distribution level ...
Approximation Algorithms for Geometric Packing Problems
We study approximation algorithms for the geometric bin packing problem and its variants. In the two-dimensional geometric bin packing problem (2D GBP), we are given n rectangular items and we have to compute an axis-parallel ...
Addressing Energy and Performance Related Challenges in Networked Embedded Systems
Networked Embedded Systems comprise of spatially and functionally distributed nodes that
are interconnected with one another and with the environment to achieve certain goals. The
nodes are connected to one another through ...
A Novel Neural Network Architecture for Sentiment-oriented Aspect-Opinion Pair Extraction
Over the years, fine-grained opinion mining in online reviews has received great attention from the
NLP research community. It involves different tasks such as Aspect Term Extraction (ATE), Opinion Term Extraction (OTE), ...
Solving Inverse Problems Using a Deep Generative Prior
In an inverse problem, the objective is to recover a signal from its measurements,
given the knowledge of the measurement operator. In this thesis, we address the
problems of compressive sensing (CS) and compressive phase ...
Scaling Blockchains Using Coding Theory and Verifiable Computing
The issue of scalability has been restricting blockchain from its widespread adoption. The
current transaction rate of bitcoin is around seven transactions/second while its size has crossed
the 300 GB mark. Although many ...
Structured Sparse Signal Recovery for mmWave Channel Estimation: Intra-vector Correlation and Modulo Compressed Sensing
This thesis contributes new theoretical results and recovery algorithms for the area of sparse signal recovery motivated by applications to the problem of channel estimation in mmWave communication systems.
The presentation ...