Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Subject "algorithms"
Now showing items 1-7 of 7
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Algorithms for various cost criteria in Reinforcement Learning
In this thesis we will look at various Reinforcement Learning algorithms. We will look at algorithms for various cost criteria or reward objectives namely Finite Horizon, Discounted Cost, Risk-Sensitive Cost. For Finite ... -
Bandit Algorithms: Fairness, Welfare, and Applications in Causal Inference
We study regret in online learning from a welfarist perspective and explore an application of bandit algorithms in causal inference. We introduce Nash regret, which measures the difference between the optimal action ... -
Infimal convolution approaches for image recovery
The quality of image captured by acquisition devices has increased drastically over the years largely due to a revolution in imaging sensor capability. But, image acquisition under low illumination continues to be a ... -
Mitigating Bias via Algorithms with Fairness Guarantees
The rapid integration of automated decision-making systems in critical domains such as resume screening, loan approval, content recommendation, and disaster containment has raised significant concerns regarding biases in ... -
Modeling of Permittivity Variations in Stochastic Computational Electromagnetics
With the evolution of 5G systems offering high data rates, major changes are required in the design approach of the components of communication systems. Furthermore, building complex electromagnetic systems at the terahertz ... -
Multi-timescale and Multi-agent Reinforcement Learning Algorithms
This thesis presents six novel works involving several research domains, such as reinforcement learning (RL)– both with or without function approximators including deep neural networks, multi-agent RL, stochastic optimization, ... -
Sequential Transfer in Multi-Armed Bandits using Reward Samples
We consider a sequential multi-task problem, where each task is modeled as a stochastic multi-armed bandit with K arms. We study the problem of transfer learning in this setting and propose algorithms based on UCB to ...