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Reinforcement Learning Algorithms for Off-Policy, Multi-Agent Learning and Applications to Smart Grids
Reinforcement Learning (RL) algorithms are a popular class of algorithms for training an agent to
learn desired behavior through interaction with an environment whose dynamics is unknown to the
agent. RL algorithms ...
Compression for Distributed Optimization and Timely Updates
The goal of this thesis is to study the compression problems arising in distributed computing
systematically.
In the first part of the thesis, we study gradient compression for distributed first-order
optimization. We ...
Machine Learning for Decoding Imagined words and Altered State of Consciousness from EEG
In the first part of the thesis, the results of our studies on the classification of phonological categories in imagined words are presented. We have investigated whether there are any statistically significant differences ...
Algorithms for Fair Clustering
Many decisions today are taken by various machine learning algorithms, hence it is crucial to
accommodate fairness in such algorithms to remove/reduce any kind of bias in the decision.
We incorporate fairness in the ...
Achieving practical secure non-volatile memory system with in-Memory Integrity Verification (iMIV)
Recent commercialization of Non-Volatile Memory (NVM) technology in the form of Intel Optane enables programmers to write recoverable programs. However, the data on NVM is susceptible to a plethora of data remanence attacks, ...
An Evaluation of Basic Protection Mechanisms in Financial Apps on Mobile Devices
This thesis concerns the robustness of security checks in financial mobile applications (or simply
financial apps). The best practices recommended by OWASP for developing such apps demand
that developers include several ...
On symmetries of and equivalence tests for two polynomial families and a circuit class
Two polynomials f, g ∈ F[x1, . . . , xn] over a field F are said to be equivalent if there exists an
n×n invertible matrix A over F such that g = f(Ax), where x = (x1 · · · xn)T . The equivalence
test (in short, ET) for ...
A Context-Aware Neural Approach for Explainable Citation Link Prediction
Citations have become an integral part of scientific publications. They play a crucial role in supporting authors’ claims throughout a scientific paper. However, citing related work is a challenging and laborious task, ...
Neural Approaches for Natural Language Query Answering over Source Code
During software development, developers need to ensure that the developed code is bug-free and the best coding practices are followed during the code development process. To guarantee this, the developers require answers ...
Perceptual Quality Assessment of Lowlight Restored and Authentically Distorted Images
The capability of hand-held devices to acquire high-definition visual content has led to a tremendous increase in the number of images and videos captured daily. However, camera hardware and pipelines are not perfect and ...