Semantic Scholar uses AI to extract papers important to this topic.
Abstract: Graph-structured data appears frequently in domains including chemistry, natural language semantics, social networks… Expand The paper investigates the acceleration of t-SNE--an embedding technique that is commonly used for the visualization of high… Expand Storing and using specific instances improves the performance of several supervised learning algorithms. These include algorithms… Expand Bagging and boosting are methods that generate a diverse ensemble of classifiers by manipulating the training data given to a… Expand Storing and using specific instances improves the performance of several supervised learning algorithms. These include algorithms… Expand Twenty-two decision tree, nine statistical, and two neural network algorithms are compared on thirty-two datasets in terms of… Expand Dynamic Bayesian Networks: Representation, Inference and Learning by Kevin Patrick Murphy Doctor of Philosophy in Computer… Expand Abstract We describe the newly written code GADGET which is suitable both for cosmological simulations of structure formation and… Expand Particle filters (PFs) are powerful sampling-based inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow… Expand We consider the following problem: Given a collection of rooted trees, answer on-line queries of the form, “What is the nearest… Expand