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| Both sides previous revisionPrevious revision | Next revisionBoth sides next revision | ||
| teaching:le-ki2-ws18 [2018/09/11 08:27] – nyga | teaching:le-ki2-ws18 [2018/09/11 08:31] – nyga | ||
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| * Probabilistische Wissensverarbeitung | * Probabilistische Wissensverarbeitung | ||
| - | * Wahrscheinlichkeitstheorie | + | * Grundlagen der Wahrscheinlichkeitstheorie |
| * Bayes' | * Bayes' | ||
| - | * Markov-Netze | + | * Markov-Netze vs. Bayes-Netze |
| * Probabilistische Klassifikation und Regression | * Probabilistische Klassifikation und Regression | ||
| Line 30: | Line 30: | ||
| * Logistic Regression | * Logistic Regression | ||
| * Bayesian Linear Regression | * Bayesian Linear Regression | ||
| + | * Classification and Regression Trees | ||
| * Probabilistisches Schließen über die Zeit | * Probabilistisches Schließen über die Zeit | ||
| + | * Stochastische Prozesse: Markov-Ketten | ||
| * Hidden Markov Models (HMM) | * Hidden Markov Models (HMM) | ||
| * Conditional Random Fields (CRF) | * Conditional Random Fields (CRF) | ||
| * Statistical Relational Learning | * Statistical Relational Learning | ||
| - | * Markov | + | * Markov |
| * Ensemble-basierte Lernalgorithmen | * Ensemble-basierte Lernalgorithmen | ||
| - | * Adaptive Boosting | + | * Adaptive Boosting |
| - | * Random Forests | + | * Gradient Tree Boosting (XGBoost) |
| + | * Bagging & Random Forests | ||
Prof. Dr. hc. Michael Beetz PhD
Head of Institute
Contact via
Andrea Cowley
assistant to Prof. Beetz
ai-office@cs.uni-bremen.de
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