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Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their ApplicationsDownload
The focus of this study is the development and evaluation of a new partially supervised learning framework. This framework belongs to an emerging field in machine learning that augments unsupervised learning processes with some elements of supervision. It is based on proximity fuzzy clustering,...
Many machine learning algorithms learn from the data by capturing certain interesting characteristics. Decision trees are used in many classification tasks. In some circumstances, we only want to consider fixed-depth trees. Unfortunately, finding the optimal depth-d decision tree can require time...
Technical report TR09-13. This article presents a survey of reinforcement learning algorithms for Markov Decision Processes (MDP). In the first half of the article, the problem of value estimation is considered. Here we start by describing the idea of bootstrapping and temporal difference...
This dissertation first introduces the concepts of robust active learning (also called optimal experimental design in statistics), and the possible advantages of it over the traditional passive learning method. Then a general regression problem with possibly misspecified models is presented, and...
The Effectiveness of Team Based Learning on Learning Outcomes in Health Professions Education: A Best Evidence for Medical Education (BEME) Systematic ReviewDownload
The aim of this systematic review was to asess the effectiveness of team based learning on improving learning outcomes in health professions education in order to provide curriculum planners with more direction in their decision-making with regard to TBL implementation.