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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 ...
Classification of Factual and Non-Factual Statements Using Adversarially Trained LSTM Networks
(2020-06-08)
Being able to determine which statements are factual and therefore likely candidates for further verification is a key value-add in any automated fact-checking system. For this task, it has been shown that LSTMs outperform ...
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 ...
GENERATING ADVERSARIAL EXAMPLES FOR RECRUITMENT RANKING ALGORITHMS
(2020-12-16)
There is no doubt that recruitment process plays an important role for both employers and applicants. Based on huge number of job candidates and open vacancies, recruitment process is expensive, time consuming and stressful ...
ADAPTIVE HUMAN-ROBOT MOTION TRANSFER FOR COMPLETE BODY IMITATION
(2022-01-06)
Programming robot systems to perform certain tasks is a big challenge especially if such programming is to be performed by persons who are not experts in robotics. For example, when programming a robot to serve as an ...