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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 ...
MACHINE LEARNING BASED DATACENTER MONITORING FRAMEWORK
(2016-12-09)
Monitoring the health of large data centers is a major concern with the ever-increasing demand of grid/cloud computing and the higher need of computational power. In a High Performance Computing (HPC) environment, the need ...
COMPARISON OF MACHINE LEARNING ALGORITHMS IN SUGGESTING CANDIDATE EDGES TO CONSTRUCT A QUERY ON HETEROGENEOUS GRAPHS
(2016-05-11)
Querying graph data can be difficult as it requires the user to have knowledge of the underlying schema and the query language. Visual query builders allow users to formulate the intended query by drawing nodes and edges ...
DWRELU : DOUBLE WEIGHTED RECTIFIER LINEAR UNIT AN ACTIVATION FUNCTION WITH TRAINABLE SCALING PARAMETER
(2018-11-14)
Deep Neural Network have become very popular for computer vision application in recent years. At the same time, it remains important to understand the different implementation choices that need to be made when designing a ...
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 ...
HEALTH MONITORING OF ATLAS DATA CENTER CLUSTERS AND FAILURE ANALYSIS
(2018-12-06)
Monitoring the health of data center clusters is an integral part of any industrial facility. ATLAS is one of the High Energy Physics experiments at the Large Hadron Collider (LHC) at CERN. ATLAS DDM (Distributed Data ...
FROM TEXT CLASSIFICATION TO IMAGE CLUSTERING, PROBLEMS LESS OPTIMIZED
(2018-06-11)
Machine Learning is thriving. Every industry is using its techniques in some way to improve their efficiency and revenue. However, the focus on research is not divided equally between all of the different areas and problems ...
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 ...