1,067 search results for “automated machine learning” in the Public website
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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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Automated detection
The results of the investigations by citizens are used in an innovative research project that investigates the potential of machine learning and automated detection in archaeology.
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Massively collaborative machine learning
Promotor: J. N. Kok, Co-promotor: A. J. Knobbe
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Artificial Intelligence & Machine Learning
Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…
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Artificial intelligence and machine learning
Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…
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Milan Koch
Science
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Automated de novo metabolite identification with mass spectrometry and cheminformatics
Promotor: Prof.dr. T. Hankemeier, Co-Promotores: T. Reijmers, L. Coulier
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Predicting alcohol use disorder through machine learning
How to come to valid risk stratification of alcohol use disorder?
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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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Vertebrate automated screening technology (VAST)
How can you use robots and automatic recognition of microscopic images to test the effect of drugs exceptionally quickly?
- SAILS Lunch Time Seminar: Towards a mathematical foundation of machine learning
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SAILS Lunch Time Seminar: Towards a mathematical foundation of machine learning
Lecture
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Crank: New methods for automated macromolecular crystal structure solution
CRANK is a novel suite for automated macromolecular structure solution and uses recently developed programs for substructure detection, refinement, and phasing.
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Automated text analysis of policy-related documentation
Political institution (like the Council of the European Union and the European Parliament) generate large bodies of text. These great amounts of text can impossibly be read by a researcher. Contrary to human researchers, computers are able to read thousands of documents a day. In this research project…
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of post-translationally modified peptides in Streptomyces with machine learning
PhD Defence
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Towards automated identification of metabolites using mass spectral trees
Promotor: Prof.dr. T. Hankemeier, Co-promotor: Dr. Theo Reijmers
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The holographic glass bead game: from superconductivity to time machines
Promotores: Prof.dr. J. Zaanen & Prof.dr. K.E. Schalm
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PNAS Paper Prize for quantum machine learning
‘We hope our paper highlights the possibilities and benefits of including artificial intelligence in quantum physics to do new discoveries.’ Vedran Dunjko of the Leiden Institute of Advanced Computer Science contributed to a paper that was published in PNAS last year and now received a Cozzarelli Prize…
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Translation Café 22 April: Machine Translation Literacy
Lecture
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Language as a time machine
By studying language you can reconstruct the history of different communities, even when no other historical sources, such as written documents, are available. In the coming years, researchers Willem Adelaar and Marian Klamer will be carrying out this kind of reconstruction in areas of great linguistic…
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Legibility in the Age of Signs and Machines
Legibility in the Age of Signs and Machines offers a compelling reflection on what the notion of legibility entails in a machinic world in which any form of cultural expression – from literary texts, films, artworks and museum exhibits to archives, laws, computer programs and algorithms – necessarily…
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Software developments in automated structure solution and crystallographic studies of the Sso10a2 and human C1 inhibitor protein
Promotor: J.P. Abrahams, Co-Promotor: N.S. Pannu
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Machine learning predicts preferences
Cláudio de Sá predicted the preferences of people using rankings. He adjusted ‘classical’ machine learning approaches, making them suitable for predicting preferences. His work can be applied in the prediction of election results. PhD defence on 16 December.
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A document classifier for medicinal chemistry publications trained on the ChEMBL corpus
Source: J Cheminform, Volume 6, Issue 1 (2014)
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Teachers’ professional learning preferences
How do secondary school teachers’ professional learning preferences relate to teaching experience and the school context?
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Frans Rodenburg
Science
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Wouter van Loon
Faculteit der Sociale Wetenschappen
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Bayesian learning: challenges, limitations and pragmatics
This dissertation is about Bayesian learning from data. How can humans and computers learn from data?
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Optimally weighted ensembles of surrogate models for sequential parameter optimization
It is a common technique in global optimization with expensive black-box functions to learn a surrogate-model of the response function from past evaluations and use it to decide on the location of future evaluations.
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Exploring Images With Deep Learning for Classification, Retrieval and Synthesis
In 2018, the number of mobile phone users will reach about 4.9 billion. Assuming an average of 5 photos taken per day using the built-in cameras would result in about 9 trillion photos annually.
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Nonverbal Learning Disorder (NLD)
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Interactive scalable condensation of reverse engineered UML class diagrams for software comprehension
Promotores: Prof.dr. J.N. Kok, Prof.dr. M.R.V. Chaudron, Co-Promotor: P. van der Putten
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Deep learning for visual understanding
With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically.
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Sleep and learning in children
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Self-learning machines for better understanding of the universe
Bright explosions appear all over the radio and gravitational-wave sky. This dynamic side of the universe which has just been discovered, can be mapped by self-learning machines. The National Science Agenda granted 5 million euro’s to CORTEX, the Center for Optimal, Real-Time Machine Studies of the…
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Collaborative learning in higher education: design, implementation and evaluation of group learning activities
The aim of this study was to provide insight into how teachers in higher education can be supported in the design, implementation and evaluation of group assignments by developing a theoretical and evidence-based framework for the design of group assignments.
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Machine Learning Improves Cross-border Tax Estimates
Multidisciplinary research has established that VAT-results are in practice six times lower than what it should have been. The new estimates rely on machine learning techniques.
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Professional learning: what teachers want to learn
The aim of this thesis was to examine what teachers want to learn themselves. The main research question was: what, how and why teachers want to learn? And does this depend on their years of teaching experience and the school at which they work?
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Increased striatal activity in adolescence benefits learning
Heightened activation of the striatum that adolescents show in response to reward is often associated with risk-taking and negative health consequences. This article in Nature Communications investigates a potential positive side of this heightened activation. It shows that the activity peak in late…
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Methods and Tools for Mining Multivariate Time Series
Mining time series is a machine learning subfield that focuses on a particular data structure, where variables are measured over (short or long) periods of time.
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Blended learning
Blended learning is all about combining face-to-face instruction with online education.
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Blended learning
The programme is also offered in a blended learning version: this is a combination of distance learning and face-to-face learning. Read more information
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Machine learning
Inaugural Lecture
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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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Self-directed learning with mobile technology in higher education
Language learners in higher education increasingly conduct out-of-class self-directed learning facilitated by mobile technology. This project aims to explore how university students use mobile technology for their self-directed language learning and investigate factors that influence their self-directed…
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Collaborative learning in teacher education: Intended, implemented and experienced curriculum
How is collaborative learning in teacher education designed and implemented? How do students experience those collaborative learning assignments? What aspects of the design and the implementation lead to which perceived learning outcomes?
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Flagships
In CCLS several subgroups have formed, below you can find an overview of these groups with the names of the leading researchers and a short outline of the project.
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Francesco Walker
Faculteit der Sociale Wetenschappen
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Chen Li
Science
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André Beijen
Faculty Governance and Global Affairs