0000000000860036

AUTHOR

Amir Hossein Akhavan Rahnama

showing 2 related works from this author

An LP-based hyperparameter optimization model for language modeling

2018

In order to find hyperparameters for a machine learning model, algorithms such as grid search or random search are used over the space of possible values of the models hyperparameters. These search algorithms opt the solution that minimizes a specific cost function. In language models, perplexity is one of the most popular cost functions. In this study, we propose a fractional nonlinear programming model that finds the optimal perplexity value. The special structure of the model allows us to approximate it by a linear programming model that can be solved using the well-known simplex algorithm. To the best of our knowledge, this is the first attempt to use optimization techniques to find per…

FOS: Computer and information sciencesMathematical optimizationPerplexityLinear programmingComputer scienceMachine Learning (stat.ML)02 engineering and technology010501 environmental sciences01 natural sciencesTheoretical Computer ScienceNonlinear programmingMachine Learning (cs.LG)Random searchSimplex algorithmSearch algorithmStatistics - Machine Learning0202 electrical engineering electronic engineering information engineeringFOS: MathematicsMathematics - Optimization and Control0105 earth and related environmental sciencesHyperparameterComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Computer Science - LearningHardware and ArchitectureOptimization and Control (math.OC)Hyperparameter optimization020201 artificial intelligence & image processingLanguage modelSoftwareInformation Systems
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Distributed Real-Time Sentiment Analysis for Big Data Social Streams

2014

Big data trend has enforced the data-centric systems to have continuous fast data streams. In recent years, real-time analytics on stream data has formed into a new research field, which aims to answer queries about "what-is-happening-now" with a negligible delay. The real challenge with real-time stream data processing is that it is impossible to store instances of data, and therefore online analytical algorithms are utilized. To perform real-time analytics, pre-processing of data should be performed in a way that only a short summary of stream is stored in main memory. In addition, due to high speed of arrival, average processing time for each instance of data should be in such a way that…

Data streamFOS: Computer and information sciencesComputer Science - Computation and LanguageComputer sciencebusiness.industryData stream miningSentiment analysisBig dataMachine Learning (stat.ML)Databases (cs.DB)Data structurecomputer.software_genreField (computer science)Computer Science - Information RetrievalTree (data structure)Computer Science - DatabasesComputer Science - Distributed Parallel and Cluster ComputingAnalyticsStatistics - Machine LearningData miningDistributed Parallel and Cluster Computing (cs.DC)businesscomputerComputation and Language (cs.CL)Information Retrieval (cs.IR)
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