1,143 search results for “machine learning” in the Public website
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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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Predicting alcohol use disorder through machine learning
How to come to valid risk stratification of alcohol use disorder?
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PhD candidate || Modelling plasma surface interactions with machine learning
Science, Leiden Institute of Chemistry (LIC)
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of post-translationally modified peptides in Streptomyces with machine learning
The ongoing increase in antimicrobial resistance combined with the low discovery of novel antibiotics is a serious threat to our health care.
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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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Research scientific programmer, Automated machine learning for spatio-temporal Earth Observation datasets
Science, Leiden Institute of Advanced Computer Science (LIACS)
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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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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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Novel system-inspired model-based quantum machine learning algorithm for prediction and generation of High-Energy Physics data
Assistant Professor Vedran Dunjko and his team received a gift from Google to support their quantum research. The research focuses on whether quantum computers can provide new ways of understanding the mysteries of high-energy physics.
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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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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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Alumnus Robert Ietswaart: ‘Machine learning is revolutionising drug discovery’
Robert Ietswaart does research into gene regulation at the famous Harvard Medical School in Boston. He developed an algorithm to better predict whether a candidate medicine is going to produce side effects. He studied mathematics and physics in Leiden, and gained his PhD in computational biology in…
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Frans Rodenburg
Science
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Wouter van Loon
Faculteit der Sociale Wetenschappen
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Florence Nightingale Colloquium
Lecture, colloquium
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Machine learning
Inaugural Lecture
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The Use of Machine Learning in Public Organizations - an Interview with PhD Student Friso Selten
Friso Selten recently started a PhD position that is part of the SAILS program. This PhD project is a collaboration between FGGA, LIACS, and eLaw, and is supervised by Bram Klievink (FGGA), Joost Broekens (LIACS), and Francien Deschene (eLaw). In the project Friso will investigate the influence of artificial…
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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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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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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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Robust rules for prediction and description.
In this work, we attempt to answer the question:
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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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Interview - ‘I learn a lot from my students’
'I am very honored to be nominated for the Teacher of the Year Award,’ says dr. Jan van Rijn. Every autumn he teaches the course Automated Machine Learning, which he set up himself at Leiden University.
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Chen Li
Science
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Surendra Balraadjsing
Science
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André Beijen
Science
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Massively Collaborative Machine Learning
PhD Defence
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Gerard van Westen
Science
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Alex Brandsen
Faculteit Archeologie
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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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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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The holographic glass bead game: from superconductivity to time machines
Promotores: Prof.dr. J. Zaanen & Prof.dr. K.E. Schalm
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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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Filter-based reconstruction methods for tomography
Promotor: K.J. Batenburg
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Aske Plaat
Science
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Novel analytical approaches to characterize particles in biopharmaceuticals
Particles are omnipresent in biopharmaceutical products. In protein-based therapeutics such particles are generally associated with impurities, either derived from the drug product itself (e.g. protein aggregates), or from extrinsic contaminations (e.g. cellulose fibers).
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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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Applied Machine Learning in Neurosurgical Oncology
PhD Defence
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Matt Young
Faculty Governance and Global Affairs
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Elise Dusseldorp
Faculteit der Sociale Wetenschappen
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Hongchang Shan
Science
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Guillermo Guerrero Egido
Science
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Daniel Vale
Faculteit Rechtsgeleerdheid
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Julian Karch
Faculteit der Sociale Wetenschappen
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Dovile Rimkute
Faculty Governance and Global Affairs
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Marjolein Fokkema
Faculteit der Sociale Wetenschappen
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Jan van Rijn
Science