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Software profiling via electromagnetic side-channel signal
(Georgia Institute of Technology, 2020-01-09)
This thesis develops general methods to exploit information leaked in Electromagnetic (EM) emanations for profiling software applications. A broad range of computing devices and software applications can benefit from these ...
Integrating independent and centralized multi-agent reinforcement learning for traffic signal network optimization
(Georgia Institute of Technology, 2019-04-30)
Traffic congestion in metropolitan areas is a world-wide problem that can be ameliorated by traffic lights that respond dynamically to real-time conditions. Recent studies applying deep reinforcement learning (RL) to ...
Performance optimizations for quantum chemistry calculations
(Georgia Institute of Technology, 2019-04-22)
Quantum chemistry is a mature area of computational science with many methods and codes developed that are used across chemistry, biochemistry, and materials science. Optimizing computational kernels in quantum chemistry ...
Towards tighter integration of machine learning and discrete optimization
(Georgia Institute of Technology, 2019-03-28)
Discrete Optimization algorithms underlie intelligent decision-making in a wide variety of domains. From airline fleet scheduling to data center resource management and matching in ride-sharing services, decisions are often ...
Identifying and clustering attack-driven crash reports using machine learning
(Georgia Institute of Technology, 2019-04-26)
We propose a tool to identify crashes caused by filed exploits from benign crashes, and cluster them based on the exploited vulnerabilities to prioritize crashes from a security point of view. The tool extracts features ...
Efficient and principled robot learning: Theory and algorithms
(Georgia Institute of Technology, 2020-01-07)
Roboticists have long envisioned fully-automated robots that can operate reliably in unstructured environments. This is an exciting but extremely difficult problem; in order to succeed, robots must reason about sequential ...
Software and algorithms for large-scale seismic inverse problems
(Georgia Institute of Technology, 2020-02-26)
Seismic imaging and parameter estimation are an import class of inverse problems with practical relevance in resource exploration, carbon control and monitoring systems for geohazards. Seismic inverse problems involve ...
Manipulating state space distributions for sample-efficient imitation-learning
(Georgia Institute of Technology, 2020-03-16)
Imitation learning has emerged as one of the most effective approaches to train agents to act intelligently in unstructured and unknown domains. On its own or in combination with reinforcement learning, it enables agents ...
Model predictive path integral control: Theoretical foundations and applications to autonomous driving
(Georgia Institute of Technology, 2019-03-21)
This thesis presents a new approach for stochastic model predictive (optimal) control: model predictive path integral control, which is based on massive parallel sampling of control trajectories. We first show the theoretical ...
Dynamic and elastic memory management in virtualized clouds
(Georgia Institute of Technology, 2019-04-02)
The memory capacity of computers and edge devices continue to grow: the DRAM capacity for low end computers are at tens or hundreds of GBs and the modern high performance computing (HPC) platforms can support terabytes of ...