915 search results for “reinforcement learning” in the Public website
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Reinforcement learning
The Reinforcement Learning lab conducts research into Reinforcement Learning and Intelligent Combinatorial Algorithms.
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2 PhD Candidates, Reinforcement Learning for Sustainable Energy
Science, Leiden Institute of Advanced Computer Science (LIACS)
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Searching by Learning: Exploring Artificial General Intelligence on Small Board Games by Deep Reinforcement Learning
In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…
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Andreas Sauter
Science
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Ili Ma
Faculteit der Sociale Wetenschappen
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Computational speedups and learning separations in quantum machine learning
This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…
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Nurbolat Kenbayev
Science
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Aske Plaat
Science
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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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*Cancelled* Mini Symposium: Reinforcement Learning
Lecture
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Alan Kai Hassen
Science
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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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Evert van Nieuwenburg
Science
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A Brief Introduction to Reinforcement Learning
Lecture
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Steven Miletic
Faculteit der Sociale Wetenschappen
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Franz Wurm
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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Collaborative learning in conservatoire education: catalyst for innovation
The aim of this research project was to increase understanding of which collaborative learning approaches already exist in conservatoire education, and how implementation of collaborative learning could be supported.
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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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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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Changing minds in social anxiety: A developmental network approach to neurocognitive bias modification
Which adolescents are more at risk of developing social anxiety disorder later in life?
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Yolinde van Paridon
Faculteit der Sociale Wetenschappen
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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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About the programme
The curriculum of this bachelor’s programme gives you an understanding of artificial intelligence and data science with a solid basis in computer science. Both artificial intelligence and data science are broad disciplines that require essential and foundational underpinnings.
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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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Faculty of Science reinforces collaboration in China
The Faculty of Science has reinforced the collaboration in China during a group trip late November. Representatives from four institutes visited ten Chinese top universities and interviewed over 130 students in PhD workshops in Beijing and Shanghai.
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Massively collaborative machine learning
Promotor: J. N. Kok, Co-promotor: A. J. Knobbe
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Nonverbal Learning Disorder (NLD)
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Programme structure
The research master's specialisation Cognitive Neuroscience consists of five main parts: the general courses, the specialisation-specific courses, the elective courses, a research internship and a thesis.
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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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Understanding deep meta-learning
The invention of neural networks marks a critical milestone in the pursuit of true artificial intelligence. Despite their impressive performance on various tasks, these networks face limitations in learning efficiently as they are often trained from scratch.
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Andreas Paraskeva
Science
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Sleep and learning in children
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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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Zsuzsika Sjoerds
Faculteit der Sociale Wetenschappen
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Faculty of Science reinforces collaboration in Indonesia
Early November, a delegation of the Faculty of Science visited two Indonesian universities to shape the collaboration in bioscience. The Faculty also opened a new Indonesian office in Yogyakarta.
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Emma Everaert
Faculteit der Sociale Wetenschappen
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Kim Stroet
Faculteit der Sociale Wetenschappen
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Julia Wasala
Science
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Exploring deep learning for multimodal understanding
This thesis mainly focuses on multimodal understanding and Visual Question Answering (VQA) via deep learning methods. For technical contributions, this thesis first focuses on improving multimodal fusion schemes via multi-stage vision-language interactions.
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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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Siuman Chung
Faculteit der Sociale Wetenschappen
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Christine Espin
Faculteit der Sociale Wetenschappen
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Elise Swart
Faculteit der Sociale Wetenschappen
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Michael Lew
Science
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Marit Guda
Faculteit der Sociale Wetenschappen
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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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Exploring Deep Learning for Intelligent Image Retrieval
This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.
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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