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ApproxML: Efficient Approximate Ad-Hoc ML Models Through Materialization and Reuse
(2019-12-10)
Machine Learning (ML) has become an essential tool in answering complex predictive analytic queries. Model building for large scale datasets is one of the most time-consuming parts of the data science pipeline. Often data ...
Convex and Non-convex Optimization Methods for Machine Learning
(2019-08-01)
This dissertation is concerned with modeling fundamental and challenging machine learning tasks as convex/non-convex optimization problems and designing a mechanism that could solve them in a cost and time-effective manner. ...
Deep Reinforcement Learning-based Portfolio Management
(2019-05-16)
Machine Learning is at the forefront of every field today. The subfields of Machine Learning called Reinforcement Learning and Deep Learning, when combined have given rise to advanced algorithms which have been successful ...
Learning Representations Using Reinforcement Learning
(2019-05-09)
The framework of reinforcement learning is a powerful suite of algorithms that can learn generalized solutions to complex decision making problems. However, the applications of reinforcement learning algorithms to traditional ...
A TWO STAGE EVENT BASED DATA DRIVEN CONTROLLER FOR IMPROVED GRASPING OF AN ARTIFICIAL HAND
(2019-07-09)
The human hand is one of the greatest (if not the greatest) tool known to mankind for grasping objects. So much so, that researchers have been investigating the development of artificial biomimetic hands in an effort to ...
MULTIVARIATE TIME SERIES PATTERN RECOGNITION USING MACHINE LEARNING AND DEEP LEARNING METHODS
(2019-12-16)
In this research work, we have implemented machine learning & deep-learning algorithms on real-time multivariate time series datasets in the manufacturing & health care fields. The research work is organized in two ...
LEARNING ROBOT MANIPULATION TASKS VIA OBSERVATION
(2019-12-06)
The coexistence of humans and robots has been the aspiration of many scientific endeavors in the past century. Most anthropomorphic or industrial robots are highly articulated and complex machines, which are designed to ...
USE OF WORD EMBEDDING TO GENERATE SIMILAR WORDS AND MISSPELLINGS FOR TRAINING PURPOSE IN CHATBOT DEVELOPMENT
(2019-12-06)
The advancement in the field of Natural Language Processing and Machine Learning has played a significant role in the huge improvement of conversational Artificial Intelligence (AI). The use of text-based conversation AI ...
Social Media Text Analysis using Multi-kernel Convolutional Neural Network
(2019-12-11)
Transportation planners and ride hailing platforms such as Uber and Lyft use their riders feedback to assess their services and monitor customer satisfaction. Social media websites such as Facebook, Instagram, LinkedIn and ...
Deep Representation Learning for Clustering and Domain Adaptation
(2019-12-05)
Representation learning is a fundamental task in the area of machine learning which can significantly influence the performance of the algorithms used in various applications. The main goal of this task is to capture the ...