1,367 search results for “machine learning” in the Public website
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Jan van Rijn
Science
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Matt Young
Faculty Governance and Global Affairs
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Dovile Rimkute
Faculty Governance and Global Affairs
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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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Tom Wilderjans
Faculteit der Sociale Wetenschappen
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Md Faysal Tareq
Science
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Bertram de Boer
Science
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Nuno De Mesquita César de Sá
Science
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Niki van Stein
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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LTP Lecture Machine Learning in Science: Just a toy?
Lecture
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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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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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On the optimization of imaging pipelines
In this thesis, topics relating to the optimization of high-throughput pipelines used for imaging are discussed. In particular, different levels of implementation, i.e., conceptual, software, and hardware, are discussed and the thesis outlines how advances on each level need to be made to make gains…
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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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High-contrast spectroscopy of exoplanet atmospheres
More than 5,000 exoplanets have been found over the past couple of decades. These exoplanets show a tremendous diversity, ranging from scorching hot Jupiters, common super-Earths, to widely separated super-Jupiters on the planet/brown dwarf boundary.
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2 PhD Candidates, Reinforcement Learning for Sustainable Energy
Science, Leiden Institute of Advanced Computer Science (LIACS)
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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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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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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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Yingjie Fan
Science
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Jian Wang
Faculteit der Sociale Wetenschappen
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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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Yolinde van Paridon
Faculteit der Sociale Wetenschappen
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PhD candidate for End-to-End Causal Learning (1.0fte)
Science, Leiden Institute of Advanced Computer Science (LIACS)
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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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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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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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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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Real-life data ask for strong algorithms: Mitra Baratchi designs them
How do we deal with large sources of greenhouse gases? Do schools provide a socially-inclusive environment for all children? And how can we protect Earth’s nature? These questions have two things in common: they are complex global challenges, and data can help answer them. Mitra Baratchi is computer…
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Babak Rezaeedaryakenari
Faculteit der Sociale Wetenschappen
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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…
- SAILS Lunch Time Seminar: Machine learning for spatio-temporal datasets + SAILS data observatory
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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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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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Automated Machine Learning for Dynamic Energy Management using Time-Series Data
PhD defence