1,284 search results for “machine learning” in the Public website
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Mert Yazan
Science
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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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'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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Niki van Stein
Science
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Bertram de Boer
Science
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Tom Wilderjans
Faculteit der Sociale Wetenschappen
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Md Faysal Tareq
Science
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Nuno De Mesquita César de Sá
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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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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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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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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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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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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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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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
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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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Yingjie Fan
Science
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Jian Wang
Faculteit der Sociale Wetenschappen
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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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Teachers’ professional learning preferences
How do secondary school teachers’ professional learning preferences relate to teaching experience and the school context?
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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.
- SAILS Lunch Time Seminar: Machine learning for spatio-temporal datasets + SAILS data observatory
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Babak Rezaeedaryakenari
Faculteit der Sociale Wetenschappen
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Learning labs in conservatoire education
Music profession requires strong reflective, collaborative, creative and improvisational skills, yet prevailing one-to-one tuition in conservatoire education focuses mainly on transmission of craft skills. Examining effects of students' collaborative and experiential learning, as in learning labs, creates…
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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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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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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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Multimodal Data and Machine Learning in the Study of Psychiatric Disorders
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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after anterior cervical discectomy: From inferential statistics to Machine Learning
PhD defence
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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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Developing methods on remote sensing detection of archaeological features in Colombia with LDE grant
A Leiden-Delft-Erasmus research team has been awarded a LDE Global Support Grant to develop reusable algorithms in the remote detection of non-orthogonal architectural features, taking place in the archaeological context of the northern extremities of the Andean, part of the Istmo-Colombian Area.
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Unraveling temporal processes using probabilistic graphical models
Real-life processes are characterized by dynamics involving time. Examples are walking, sleeping, disease progress in medical treatment, and events in a workflow.
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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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Tim van Erven makes computers even smarter
In high school, Tim van Erven read about an artificially intelligent algorithm that could solve mazes. From that moment on, he was sold: ‘There’s something magical about algorithms. With a list of fixed rules you can make them learn the most diverse things.’ This year, he won a Vidi grant, which he…