1,323 search results for “machine learning” in the Public website
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BNAIC/Benelearn conference big success
Reinforcement learning, agents and classification: these are just some of the topics researchers on Artificial Intelligence and Machine Learning discussed at the BNAIC/BeneLearn conference 2020. It was the first time Leiden University hosted the annually held Belgium Netherlands Artificial Intelligence…
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Holger Hoos in NRC about AI brain drain
Dutch newspaper NRC contacted four Dutch universities regarding the brain drain in the field of Artificial Intelligence (AI) that is going on in the Netherlands.
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Calculated Moves: Generating Air Combat Behaviour
By training with virtual opponents known as computer generated forces (CGFs), trainee fighter pilots can build the experience necessary for air combat operations, at a fraction of the cost of training with real aircraft.
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Niki van Stein
Science
n.van.stein@liacs.leidenuniv.nl | +31 71 527 2727
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Bertram de Boer
Science
b.f.de.boer@cml.leidenuniv.nl | +31 71 527 2727
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Tom Wilderjans
Faculteit der Sociale Wetenschappen
t.f.wilderjans@fsw.leidenuniv.nl | +31 71 527 6058
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Md Faysal Tareq
Science
m.f.tareq@cml.leidenuniv.nl | +31 71 527 2727
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Nuno De Mesquita César de Sá
Science
n.q.de.mesquita.cesar.de.sa@cml.leidenuniv.nl | +31 71 527 2727
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'Europe loses AI battle'
Europe falls behind China and the United States in the field of artificial intelligence (AI), which creates a brain drain for talented students and scientists. A high standard research institute for AI can turn the tide, claims initiator Holger Hoos, Professor of Machine Learning.
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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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LTP Lecture Machine Learning in Science: Just a toy?
Lecture
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Radiomics-based machine learning classification of bone chondrosarcoma
PhD defence
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Computational speedups and learnability in quantum machine learning
PhD defence
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Machine Learning and Computer Vision for Urban Drainage Inspections
PhD defence
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Reliable and Fair Machine Learning for Risk Assessment
PhD defence
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From data to discoveries: machine learning and optimization in space
Lecture
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TAILOR - Trustworthy AI through the integration of learning
The quest for Trustworthy AI is high on both the political and the research agenda, and it actually constitutes TAILOR’s first research objective (H1) of developing the foundations for Trustworthy AI. It is concerned with designing and developing AI systems that incorporate the safeguards that make…
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European grant to advance self-learning capabilities of quantum computers
A major grant for research into machine learning algorithms for quantum computers. With this ERC Consolidator grant, Vedran Dunjko and his colleagues hope to discover which real-world problems a quantum computer can solve faster than a normal one.
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Proteins in harmony: Tuning selectivity in early drug discovery
This thesis describes the importance of being able to control the selectivity of potential drug candidates.
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Transforming data into knowledge for intelligent decision-making in early drug discovery
Promotor: A.P.IJzerman Co-promotor: A. Bender
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Learning-based Representations of High-dimensional CAE Models for Automotive Design Optimization
In design optimization problems, engineers typically handcraft design representations based on personal expertise, which leaves a fingerprint of the user experience in the optimization data. Thus, learning this notion of experience as transferrable design features has potential to improve the performance…
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Sparsity-Based Algorithms for Inverse Problems
Inverse problems are problems where we want to estimate the values of certain parameters of a system given observations of the system. Such problems occur in several areas of science and engineering. Inverse problems are often ill-posed, which means that the observations of the system do not uniquely…
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ECOLE: Experience-based COmputation: Learning to optimisE
Researchers of the Leiden Institute of Advanced Computer Science (LIACS) will develop a training programme the next generation of early stage researchers (ESRs). During a four years project they will be trained to approach industrial challenges in a holistic manner by developing solutions in an automotive…
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Hunting for the fastest stars in the Milky Way
The high velocity tail of the total velocity distribution of stars provides essential insight into fundamental properties of the Galaxy.
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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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2 PhD Candidates, Reinforcement Learning for Sustainable Energy
Science, Leiden Institute of Advanced Computer Science (LIACS)
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Towards High Performance and Efficient Brain Computer Interface Character Speller: Convolutional Neural Network based Methods
A P300-based Brain Computer Interface character speller, also known as P300 speller, has been an important communication pathway, under extensive research, for people who lose motor ability, such as patients with Amyotrophic Lateral Sclerosis or spinal-cord injury because a P300 speller allows human-beings…
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Algorithms combat environmental pollution from ships
Did you know that algorithms can help with the prevention of air pollution and ships sinking in the sea? A team of Leiden University researchers have worked together with the Dutch Ministry of Infrastructure and Water Management to look in data-driven inspection of ships. In this interview, Gerrit Jan…
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XR (Extended Reality) to learn global challenges
Development of effective VR training for International Law of Armed Conflict (ILAC)
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Yolinde van Paridon
Faculteit der Sociale Wetenschappen
y.van.paridon.3@fsw.leidenuniv.nl | +31 71 527 1488
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Yingjie Fan
Science
y.fan@liacs.leidenuniv.nl | +31 71 527 4799
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Jian Wang
Faculteit der Sociale Wetenschappen
j.wang@cwts.leidenuniv.nl | +31 71 527 2727
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To explore the drug space smarter: Artificial intelligence in drug design for G protein-coupled receptors
Over several decades, a variety of computational methods for drug discovery have been proposed and applied in practice. With the accumulation of data and the development of machine learning methods, computational drug design methods have gradually shifted to a new paradigm, i.e. deep learning methods…
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EPP meta-measure and rethinking machine learning benchmarks: A recipe for meta-learning success?
Lecture
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Machine Learning and Deep Learning Approaches for Multivariate Time Series Prediction and Anomaly Detection
PhD defence
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Webinars
On this page you will find a collection of presentations and videos of the Florence Nightingale Colloquia, seminars at the faculty and other event recordings hosted by the Data Science Research Programme.
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Babak Rezaeedaryakenari
Faculteit der Sociale Wetenschappen
s.rezaeedaryakenari@fsw.leidenuniv.nl | +31 70 800 3687
- SAILS Lunch Time Seminar: Machine learning for spatio-temporal datasets + SAILS data observatory
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Pascal chair 2023
Peter Flach is Professor of Artificial Intelligence at the University of Bristol. An internationally leading scholar in the evaluation and improvement of machine learning models using ROC analysis and calibration, he has also published on mining highly structured data, on knowledge-driven and explainable…
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Tessa Verhoef: 'An algorithm still has a lot to learn from human interaction'
If an algorithm has to learn to understand language, simply having a lot of data doesn’t help much. Like us, a computer has to learn the language in interaction with others. Tessa Verhoef is fascinated by how this interaction works.
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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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Socially Embedded AI Systems
This interdisciplinary research project explores several adaptive machine learning methods which can give insight into the interaction between human and machine. The ultimate goal is open and natural communication between humans and AI that should result in mutual trust, cooperation and coordination…
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Automated Machine Learning for Dynamic Energy Management using Time-Series Data
PhD defence
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sarcoma and non-sarcoma clinical data with statistical methods and machine learning techniques
PhD defence
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Multimodal Data and Machine Learning in the Study of Psychiatric Disorders
PhD defence
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after anterior cervical discectomy: From inferential statistics to Machine Learning
PhD defence
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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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The search for a ‘quantum advantage’
Proving a quantum computer to be quicker than a normal one is one step closer. After a breakthrough in speeding up classical algorithms, researchers Vedran Dunjko and Casper Gyurik showed that only one quantum algorithm could beat its classical counterpart. They discuss their discovery in Quanta Mag…
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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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Artifical intelligence gets a boost from quantum computing
Machine learning - on classical computers- has made great progress in the past five years. Computer translation of speech and text is just one example. In Leiden, some researchers expect that machine learning, empowered by quantum systems, even if they only contain a few dozen qubits, can lead to a…