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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 ...
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 ...
Operating System Support for Efficient Virtual Memory
Computers rely on the virtual memory abstraction to simplify programming, portability, physical memory management and ensure isolation among co-running applications. However, it creates a layer of indirection in the ...
Performance Characterization and Optimizations of Traditional ML Applications
Even in the era of Deep Learning based methods, traditional machine learning methods with large data sets continue to attract significant attention. However, we find an apparent lack of a detailed performance characterization ...
Recovery Algorithms for planted structures in Semi-random models
For many NP-hard problems, the analysis of best-known approximation algorithms yields “poor” worst-case guarantees. However, using various heuristics, the problems can be solved (to some extent) in real-life instances. ...