[PDF] Top 20 Computing procedures for a learning machine

Computing procedures for a learning machine

... An optimal path from node i to node j has the lowest cost over all possible paths from node i to node jo An admissible algorithm considers only the set of arc costs it has to work with s[r] ... See full document

231

Artificial Intelligence in Predicting Stroke

... effective learning and adaptation model, it provides solutions to several engineering ...DNA computing and Quantum computing among several ...for machine to adapt to the recent trend in the ... See full document

6

An image analysis and machine learning approach to measuring the quality of individual colonoscopy procedures

... colonoscopy procedures, due to the use of a training model and the lack of suction ...colonoscopic procedures, whether mainly done for screening purposes or for thera- peutic ...the procedures were ... See full document

167

International Journal of Computer Science and Mobile Computing

... for machine learning algorithms that incorporate human input and enable the user to take control at specific points during the execution of the learned ... See full document

5

Intersection of HPC and Machine Learning

... parallel machine learning on the Java Virtual Machine (JVM) using an Intel Haswell HPC cluster with 24 or 36 cores per ...parallel computing in order to optimize the Java parallel programming ... See full document

5

Optimization of Machine Learning Process Using Parallel Computing

... In this paper it was proven that PC can be efficiently used for the improvement of reaching good quality results of supervised learning. The experiments on image recognition, run on five sets of empirical data, ... See full document

7

A Study On Cognitive Computing Methodologies For Intelligent Decision Making And Problem Solving

... fusion, machine learning algorithm for hypothesis generation, evidence gathering and assign score to hypothesis, domain cognitive model for processing specific domain along with learning component to ... See full document

5

Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computing

... Learning Everywhere: Motivation and Classification Molecular Science Examples ○ Adaptive Sampling: Predicting go next in MD MLaroundHPC ○ Using deep learning approaches for MD trajectory[r] ... See full document

24

The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures

... machine learning models for automatic extraction of materials syntheses from text, in this work we present a new dataset of synthesis procedures anno- tated with semantic structure by domain experts ... See full document

9

Smart Hospital concept and its implementation capabilities based on the incentive extension

... technologies-cloud computing, IoT, Big data, predictive analytics, machine learning and artificial intelligence, block chain technologies and mobile technologies - combined with the "4P" ... See full document

7

Classification of Diabetes Mellitus using Soft Computing and Machine Learning Techniques

... sicknesses. The work can be extended and upgraded for the computerization of diabetes exam inclusive of a few other AI estimations. [2] different statistics mining method and its software have been inspected or ... See full document

5

TOWARDS HPC AND BIG DATA CONVERGENCE IN A COMPONENT BASED APPROACH

... Data-driven computing frameworks are still in the early stages, and as we discussed there are four driving application areas (streaming, data pipelines, machine learning, and service) with different ... See full document

226

Machine learning on normalized protein sequences

... The focus of the current study is to compare the sim- ple linear interpolation [16] with non-linear normaliza- tion procedures in order to evaluate the performance in subsequent classification. To this end, we ... See full document

10

A Review on Machine Learning Based Resource Allocation in Cloud Computing

... the machine learning algorithm to find a better mapping ...the machine learning based mechanism can reduce the computation overhead in a considerable ... See full document

11

Proposed Improvements For Automated Chemical Safety Evaluations Using In-Silico Techniques

... in machine-learning (ML) due to advances in hardware and the dividends of networked research-communities coming into fruition in the form of enriched datasets, researchers can now correctly leverage ... See full document

8

Convergence Of Cloud Computing, Internet Of Things, And Machine Learning: The Future Of Decision Support Systems

... One of the many technology fields that has been present for a while is the Decision Support Systems (DSS), which has evolved to become business intelligence (BI). DSS can be traced back to early 1970s when Scott-Morton ... See full document

6

Computing methodologies Machine learning Artificial intelligence

... singing voice systems — Decision Tree, Random Forest and Convolution neural Network and provided explanation towards the behavior of the model. aLIME for Anchor Local Interpretable Model-Agnostic Explanations is also an ... See full document

15

Machine Learning and High Performance Computing

... Improving Simulation with Configurations and Integration of Data MLAutoTuningHPC: Learning Configurations • This is classic Autotuning and one optimizes some mix of performance and quali[r] ... See full document

36

Weather Prediction using Linear Regression & Support Vector Machine vide Big Data

... The Linear regression only shows the 2-dimensional model based on confusion matrix case where the data points are linearly separable. The mathematics of the problem to be solved is the following Support Vector ... See full document

10

Analyzing algorithm precision for Stock Market datasets

... in Machine Learning which have a varied usage ...Vector Machine, Naïve Bayes, K-Means, Dimensionality Reduction, Markov Decision process, etc are some of the algorithms available for various aspects ... See full document

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