1,154 search results for “data learning” in the Public website
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Statistical learning for complex data to enable precision medicine strategies
Explaining treatment response variability between and within patients can support treatment and dosing optimization, to improve treatment of individual patients.
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Data-Driven Machine Learning and Optimization Pipelines for Real- World Applications
Machine Learning is becoming a more and more substantial technology for industry.
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Integrating data to learn more
Tremendous amounts of data are generated in scientific research each day. Most of this data has more potential than we are using now, says Katy Wolstencroft, assistant professor in bioinformatics and computer science. We just need to integrate and manage it better.
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Wouter van Loon
Faculteit der Sociale Wetenschappen
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Deep learning for tomographic reconstruction with limited data
Tomography is a powerful technique to non-destructively determine the interior structure of an object.Usually, a series of projection images (e.g.\ X-ray images) is acquired from a range of different positions.
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Teachers' use of progress data in planning and evaluating instruction for students with learning disabilities
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The flux and flow of data: connecting large datasets with machine learning in a drug discovery envirionment
This thesis focuses on data found in the field of computational drug discovery. New insight can be obtained by applying machine learning in various ways and in a variety of domains. Two studies delved into the application of proteochemometrics (PCM), a machine learning technique that can be used to…
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Stacked Domain Learning for multi-domain data: a new ensemble method
The aim of this project is to develop accurate but interpretable ensemble learning methods for high-dimensional multi-domain data.
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Data-Driven Risk Assessment in Infrastructure Networks
Leiden University and the Ministry of Infrastructure and Water Management are involved in a collaboration in the form of a research project titled 'Data-Driven Risk Assessment in Infrastructure Networks'.
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Exploring big data approaches in the context of early stage clinical
Als gevolg van de grote technologische vooruitgang in de gezondheidszorg worden in toenemende mate gegevens verzameld tijdens de uitvoering van klinische onderzoeken.
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Machine learning-based NO2 estimation from seagoing ships using TROPOMI/S5P satellite data
The marine shipping industry is one of the strongest emitters of nitrogen oxides (NOx), a pollutant detrimental to ecology and human health. Over the last 20 years, the pollution produced by power plants, the industry sector, and cars has been decreasing.
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Data-driven donation strategies: understanding and predicting blood donor deferral
The research in this dissertation aims to optimise blood donation processes in the framework of the Dutch national blood bank Sanquin. The primary health risk for blood donors is iron deficiency, which is evaluated based on donors' hemoglobin and ferritin levels.
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Automated machine learning for dynamic energy management using time-series data
Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…
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Vincent Croft-
Science
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Massively collaborative machine learning
Promotor: J. N. Kok, Co-promotor: A. J. Knobbe
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The use of Deep Learning in the automated detection of archaeological objects in remotely sensed data
Generally the data from remote sensing surveys - the scanning of the earth by satellite or aircraft in order to obtain information about it - is screened manually in archaeology. However, constant monitoring of the earth's surface causes a huge influx of data of high complexity and high quality. To…
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‘For good measure’: data gaps in a big data world
Sarah Giest and Annemarie Samuels, both Assistant Professors at Leiden University, researched the quality and coverage of the data being collected for policiymakers to be used, specifically pertaining to minority groups.
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Matthijs van Leeuwen
Science
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Julian Karch
Faculteit der Sociale Wetenschappen
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Inaugural lecture: Data of Value
By comparing individual health data with population data, doctors can provide personalized health advice and patients can learn from each other's experiences. Wessel Kraaij, professor of Applied Data Analytics shows how personal data can have predictive value.
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DAMIOSO - data mining on high volume simulation output
Modern computer-aided simulation tools used by various industries produce gigabytes of data. But currently, they take days and even up to weeks of computation effort. To make the best use of all these data, the DAMIOSO project focuses on developing algorithms and tools for managing, mining, and optimizing…
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Data science
The majority of scientists, from archaeologists through to zoologists, collect enormous volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics and computer science, we can develop algorithms for analyzing…
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Multi-dimensional feature and data mining
In this thesis we explore machine and deep learning approaches that address keychallenges in high dimensional problem areas and also in improving accuracy in wellknown problems. In high dimensional contexts, we have focused on computational fluid dynamics (CFD) simulations.
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Aske Plaat
Science
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Data Driven Modeling & Optimization of Industrial Processes
Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.
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Explainatory Data Analysis
The Explainatory Data Analysis group develops algorithms and theory that enable domain experts to explain data by finding interpretable patterns and models.
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Data Science
The majority of scientists, from archaeologists through to zoologists, collect huge volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics, we can develop algorithms for analysing and identifying patterns…
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Statistics and Data Science
Are you thinking about studying Statistics and Data Science? Learn more and watch the introduction video.
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Guilherme D'Andrea Curra
Faculteit Archeologie
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Zihao Yuan
Science
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Data Science
The ability to collect and interpret huge quantities of data has become indispensable to society and academia. Leiden University is a knowledge and expertise centre for data science that places the emphasis on interdisciplinary collaboration and innovation.
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Data Science: Computer Science (MSc)
The master's specialisation Data Science: Computer Science at Leiden University provides students thorough knowledge and understanding of statistical and computational aspects of data analysis, including their application in databases, advances in data mining, networks, pattern recognition, and deep…
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Data Management
LACDR adheres to strict data management rules, with the aim to make our data findable, accessible, interoperable and re-usable. For this reason all LACDR PhD candidates are required to prepare a data management plan and to implement data management rules accordingly. All PhD candidates follow a data…
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Data Mining and Sports
Collecting data in sports increased in importance the last few years.
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Tom Wilderjans
Faculteit der Sociale Wetenschappen
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Mariëlle Linting
Faculteit der Sociale Wetenschappen
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Publication Helena Ursic en Bart Custers about data reuse
Data reuse and big data: a taxonomy for personal data reuse.
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SAPPAO - Optimizing the flight times of airplanes using data science
The SAPPAO project aims to optimise the accuracy and reliability of predicting scheduled flight times. The full name of the project is 'A Systems Approach towards Data Mining and Prediction in Airlines Operations'.
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Data
Data Sets Department of Economics
- Data Science & Artificial Intelligence
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Daniel Vale
Faculteit Rechtsgeleerdheid
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Governance and Data Science Group
The extensive use of electronic communication channels and other devices has opened new possibilities for collecting data on human behavior. This information is sometimes openly accessible, but largely part of administrative registration systems that are not open to the broader public. The data provides…
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Risk bounds for deep learning
In this thesis, deep learning is studied from a statistical perspective. Convergence rates for the worst case risk bounds of neural network estimators are obtained in the classification, density estimation and linear regression model.
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Data-driven Predictive Maintenance and Time-Series Applications
Predictive maintenance (PdM) is a maintenance policy that uses the past, current, and prognosticated health condition of an asset to predict when timely maintenance should occur.
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Computational speedups and learning separations in quantum machine learning
This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…
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Exploratory Data Mining in Multimodal data
The change from a closed institution to an open living environment for patients with late stages of dementia will give the patients more freedom in their day-to-day life. The effect of this change on the patients’ mobility, activity and interaction with others will be assessed with sensor technology…
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Applied Data Science Lab
Although science and education have top priority, exploratory projects with companies, governments and NGOs generate ample opportunities in terms of societal challenges, science strategy, valorisation and research collaboration. In the LIACS Applied Data Science Lab, our master's students and graduates…
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Data-Driven Drug Discovery Network (D4N)
The Data-Driven Drug Discovery Network (D4N) is an initiative by researchers from Leiden University and collaborators to join efforts in applying and developing novel techniques from data science to drug discovery and related topics from bioinformatics.
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From Data to insight
Social science research helps us understand human behaviour and social structures. These are determined by various factors, which makes the research complex and increases the likelihood of drawing the wrong conclusions. The choice of research method and analysis is therefore extremely important. It…
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FAIR data
Open Science means not only sharing final research results but also the underlying data. A main way to do that is by making research data FAIR: Findable, Accessible, Interoperable and Reusable.