Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Subject "machine learning"
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Efficient Algorithms for Learning Restricted Boltzmann Machines
The probabilistic generative models learn useful features from unlabeled data which can be used for subsequent problem-specific tasks, such as classification, regression or information retrieval. The RBM is one such important ... -
Multimodal sleep staging and diagnosis of sleep disorders
Sleep is not a single uniform state, but rather a cyclical pattern involving multiple stages such as rapid eye movement (REM) and non-REM (NREM stages N1, N2, and N3). Polysomnography (PSG) is considered as the gold standard ... -
On Policy Gradients, Momentum, and Learning with Adversaries: Algorithms and Convergence Analysis
This thesis comprises five works, organized into three parts: the first focuses on average-reward Reinforcement Learning (RL), the second on distributed learning under adversaries in heterogeneous and asynchronous setups, ...