Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Subject "Machine learning"
Now showing items 1-6 of 6
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Decision Making under Uncertainty : Reinforcement Learning Algorithms and Applications in Cloud Computing, Crowdsourcing and Predictive Analytics
In this thesis, we study both theoretical and practical aspects of decision making, with a focus on reinforcement learning based methods. Reinforcement learning (RL) is a form of semi-supervised learning in which the agent ... -
Deep Learning Methods For Audio EEG Analysis
The perception of speech and audio is one of the defining features of humans. Much of the brain’s underlying processes as we listen to acoustic signals are unknown, and significant research efforts are needed to unravel ... -
Efficient Algorithms for Structured Output Learning
(2018-05-08)Structured output learning is the machine learning task of building a classifier to predict structured outputs. Structured outputs arise in several contexts in diverse applications like natural language processing, computer ... -
Imitation Learning Techniques for Robot Manipulation
Robots that can operate in unstructured environments and collaborate with humans play a major role in raising productivity and living standards as societies age. Unlike the robots currently used in industrial settings for ... -
Learning to Adapt Policies for uSD card
Machine Learning(ML) for Systems is a new and promising research area where performance of computer systems is optimized using machine learning methods. ML for Systems has outperformed traditional heuristics methods in ... -
Statistical Network Analysis: Community Structure, Fairness Constraints, and Emergent Behavior
Networks or graphs provide mathematical tools for describing and analyzing relational data. They are used in biology to model interactions between proteins, in economics to identify trade alliances among countries, in ...