scalable algorithms
Scalable Algorithms in the Cloud I
... Valid on Clouds and traditional clusters – Apache Hadoop, Google MapReduce, Microsoft Dryad, Bigtable, Chubby and others – MapReduce designed for information retrieval/e-commerce search,[r] ...
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Classification with Large Sparse Datasets: Convergence Analysis and Scalable Algorithms
... Classifying large sparse data is important in many real-world applications, such as to predict users’ gender and profitability based on product ratings. Traditionally, such datasets are often classified with linear ...
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Scalable Algorithms for Mining Dynamic Graphs and Hypergraphs with Applications to Anomaly Detection.
... Finding subgraphs with irregular behavior requires an approach different from the ones for anomalous vertices or edges, since enumerating every possible subgraph in even a single graph is an intractable problem. Hence, ...
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Scalable Algorithms in the Cloud II
... • Application: Large models (e.g., neural networks with more neurons and connections) combined with large datasets are increasingly the top performers in benchmark tasks for vision, speech, and Natural Language ...
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The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale
... designing algorithms and for mapping the associated com- putational patterns onto the available architectures – from the processor to system level – are needed (Lawrence et ...the algorithms used in NWP ...
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Scalable Algorithms in the Cloud III
... Python or REST API User in Project User in Project CMPlan CMPlan CMProv CMProv CMMon CMMon Infrastructure (Cluster, Storage, Network, CPS) Infrastructure (Cluster, Storage, Netw[r] ...
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ABSTRACT : The process of extracting knowledge from the large volumes of data is data mining is a crucial step in
... Many algorithms are available to analysis data in ...and scalable algorithms to analyse massive datasets, how to interpret and visualize the results, and how to model and support the interaction ...
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Co evolving memetic algorithms: A learning approach to robust scalable optimisation
... Abstract- This paper presents and examines the be- haviour of a system whereby the rules governing lo- cal search within a Memetic Algorithm are co-evolved alongside the problem representation. We describe the rationale ...
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BudgetedSVM: A Toolbox for Scalable SVM Approximations
... proposed algorithms for scalable training of Support Vector Machine (SVM) ap- proximators: Adaptive Multi-hyperplane Machines, Low-rank Linearization SVM, and Budgeted Stochastic Gradient ...
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Hinge-Loss Markov Random Fields and Probabilistic Soft Logic
... The previous two subsections showed that the same convex program can approximate MAP inference in discrete, logic-based models, whether viewed from the perspective of randomized algorithms or variational methods. ...
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Research on the Application of Frequent Item Mining in Credit Risks
... relevant algorithms for mining frequent ...and Scalable Bloom Filter based on Landmark window model (FI-ESBFL), which deeply explores the essentials of data stream frequent item mining algorithm over ...
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Big Data Vs Traditional Data
... Query Processing, Data Mining, Analysis Mining in Big Data necessitates cleaned, integrated, trustworthy, and efficiently accessible data, , scalable mining algorithms ,declarative query[r] ...
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LIBOL: A Library for Online Learning Algorithms
... The design principle is to keep the package simple, easy to read and extend. All codes follow the MATALB standards with core functions implemented in C/C++. It generally needs no external libraries, except for the ...
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Highly Secure Scalable Compression of Encrypted Images using Chaos and AES Algorithms
... The current work focuses on designing a scalable compression scheme of stream cipher encrypted images, where encryption is carried out by applying a stream cipher in the standard format. Stream ciphers are an ...
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Stochastic gradient Markov chain Monte Carlo
... these algorithms is that, while producing consistent estimates and satisfying a central limit theorem (Teh et ...MCMC algorithms. In recent years, stochastic gradient MCMC algorithms have become a ...
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Review on Ant Colony Optimization and Zone Based Routing Protocols in MANET
... ABSTRACT: Mobile Ad Hoc Network (MANET) is a collection of wireless mobile nodes dynamically forming a network. There is no fix infrastructure in MANETs. Any time node can join or leave network because no centralized ...
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Perinatal Hypoxia Diagnostic System by using Scalable Machine Learning Algorithms
... The right inference of CTG records can help in the early-stage prediction of fetal condition. This study aimed to imitate a solution using big data with various machine learning algorithms like SVM, RF. Simple SVM ...
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Anchors Regularized: Adding Robustness and Extensibility to Scalable Topic Modeling Algorithms
... offer scalable alternatives to Markov chain Monte Carlo and expec- tation ...efficient algorithms more flexible; we also show that these methods can be com- bined with informed ...
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Efficient Multicast Routing Algorithms for Scalable Wireless Network
... existing algorithms to link the source with the destination is purely random propagation, which uses more number of repeater nodes and looping leading to the consumption more power, which is ...
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Scalable Methods and Algorithms for Very Large Graphs Based on Sampling
... This dissertation proposed efficient methods to estimate the number of triangles and clustering coefficient in network graphs. Counting the number of triangles and com- puting clustering coefficient are fundamental ...
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