Browsing by Subject "Machine learning"
Now showing items 1-11 of 11
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Accelerated Search of Catalysts Using Density Functional Theory and Machine Learning
The need for clean and renewable energy resources has propelled the interest in designing new catalysts producing energy from renewable resources and alternate cleaner fuels such as hydrogen, methane, ammonia, ethylene, ... -
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 ... -
Evaluating routine biochemical parameters for breast cancer detection in Indian women: A machine learning approach
Breast cancer stands as the leading cancer type among Indian women, with a mortality rate that surpasses that of nations such as the USA, Australia, and the UK. The higher mortality rate is largely explained by a lack of ... -
Exploration of exfoliation, functionalization and properties of MXenes via first-principles and machine learning
The monolayers of early transition metal carbides and carbonitrides named MXenes are exfoliated from the corresponding bulk MAX phases (Mn+1AXn, M = early transition metal, A = group IIIA or IVA element and X = carbon ... -
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 ... -
Network models uncover key molecular perturbations in complex human diseases
Biological systems are complex networks of molecular components that function in a tightly controlled manner. Any form of perturbation in these components or their associated interactions affects the normal physiology of ... -
Novel Neural Architectures based on Recurrent Connections and Symmetric Filters for Visual Processing
Artificial Neural Networks (ANN) have been very successful due to their ability to extract meaningful information without any need for pre-processing raw data. First artificial neural networks were created in essence to ... -
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 ...