204.674 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
Identifying Real Estate Opportunities Using Machine Learning
…home faster, for various reasons. In this paper, we aim at developing a machine learning application that identifies opportunities in the real estate market in real time, i.e., houses that are listed with a price substantially below the market price. This program can be useful for investors…
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Cell Fault Management Using Machine Learning Techniques
This paper surveys the literature relating to the application of machine learning to fault management in cellular networks from an operational perspective. We summarise the main issues as 5G networks evolve, and their implications for fault management. We describe the relevant machine learning…
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BESIII Drift Chamber Tracking with Machine Learning
The tracking efficiency and the quality for the drift chamber of the BESIII experiment is essential to the physics analysis. The tracking efficiency of the drift chamber of BESIII is high for the high momentum tracks but still have room to improve for the low momentum tracks, especially for the…
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Application of Machine Learning for Cytometry Data
…dimensionality, large cell numbers, and heterogeneity between datasets. Machine learning techniques are well suited to analyze complex cytometry data and have been used in multiple facets of cytometry data analysis, including dimensionality reduction, cell population identification, and sample…
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Machine learning in knee osteoarthritis: A review
Summary: Objective: The purpose of present review paper is to introduce the reader to key directions of Machine Learning techniques on the diagnosis and predictions of knee osteoarthritis. Design: This survey was based on research articles published between 2006 and 2019. The articles were divided…
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Cyberbullying severity detection: A machine learning approach.
…information technique. Based on these features, we developed a supervised machine learning solution for cyberbullying detection and multi-class categorization of its severity in Twitter. In the study we applied Embedding, Sentiment, and Lexicon features along with PMI-semantic orientation…
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Machine Learning in Proof General: Interfacing Interfaces
We present ML4PG - a machine learning extension for Proof General. It allows users to gather proof statistics related to shapes of goals, sequences of applied tactics, and proof tree structures from the libraries of interactive higher-order proofs written in Coq and SSReflect. The gathered data is…
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Tackling Photonic Inverse Design with Machine Learning
Abstract Machine learning, as a study of algorithms that automate prediction and decision‐making based on complex data, has become one of the most effective tools in the study of artificial intelligence. In recent years, scientific communities have been gradually merging data‐driven approaches with…
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Adaptive Safe Semi-Supervised Extreme Machine Learning
Semi-supervised learning (SSL) based on manifold regularization (MR) is an excellent learning framework. However, the performance of SSL heavily depends on the construction of manifold graph and the safety degrees of unlabeled samples. Due to the construction of manifold graph and safety degrees of…
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Experimental Evaluation of Quantum Machine Learning Algorithms
Machine learning and quantum computing are both areas with considerable progress in recent years. The combination of these disciplines holds great promise for both research and practical applications. Recently there have also been many theoretical contributions of quantum machine learning…
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Real estate valuation using machine learning techniques
In this work, the methods of artificial intelligence are analyzed in order to perform a more accurate value prediction of the apartments sold in Vilnius city and district. The work uses publicly available information about apartments put for sale on Aruodas.lt, which is collected in an automated…
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Estimating Ocean Surface Currents With Machine Learning
…un-physical estimate of the surface flow. In this study we explore Machine Learning (ML) algorithms as an alternate route to infer surface currents from satellite observable quantities. We train our ML models with SSH, SST, and wind stress from available primitive equation ocean GCM simulation…
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Machine learning reveals orbital interaction in materials
We propose a novel representation of materials named an ‘orbital-field matrix (OFM)’, which is based on the distribution of valence shell electrons. We demonstrate that this new representation can be highly useful in mining material data. Experimental investigation shows that the formation energies…
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Machine learning in Neutrosophic Environment: A Survey
…stage. However, this paper summarizes all works done about mapping machine learning algorithms from crisp number space to Neutrosophic environment. We discuss also contributions and hybridization of machine learning algorithms with Single-valued Neutrosophic numbers (SVNs) in modeling imperfect…
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Event Classification with Multi-step Machine Learning
The usefulness and value of Multi-step Machine Learning (ML), where a task is organized into connected sub-tasks with known intermediate inference goals, as opposed to a single large model learned end-to-end without intermediate sub-tasks, is presented. Pre-optimized ML models are connected and…
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Artikel Jurnal Teks lengkap
Machine learning for surface prediction in ACTS
We present an ongoing R&D activity for machine-learning-assisted navigation through detectors to be used for track reconstruction. We investigate different approaches of training neural networks for surface prediction and compare their results. This work is carried out in the context of the ACTS…
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Machine Learning Analysis of Binaural Rowing Sounds
Techniques for machine hearing are increasing their potentiality due to new application domains. In this work we are addressing the analysis of rowing sounds in natural context for the purpose of supporting a training system based on virtual environments. This paper presents the acquisition…
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