Tutorials

Monday, September 7 (half day tutorials)

Learning from Multi-label Data (morning)

Grigorios Tsoumakas (Aristotle University of Thessaloniki) , Min Ling Zhang (Hohai University) and Zhi-Hua Zhou (Nanjing University)

Keywords: problem transformation and algorithm adaptation, exploiting label structure, learning with large number of labels, multi-instance multi-label learning, the Mulan open-source software, real-world applications.

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Language and Document Analysis: Motivating Latent Variable Models (morning)

Wray Buntine (NICTA, Helsinki Institute of IT)

Keywords: natural language processing and linguistics, document analysis, information access, latent variable models, topic models.

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Methods for Large Network Analysis (afternoon)

Vladimir Batagelj (University of Ljubljana)

Keywords: large networks, connectivity, network condensation, properties of vertices/lines, islands, two-mode network, pattern search (motifs), triadic spectrum, clustering in large networks., visualization of large networks.

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Friday, September 11 (half day tutorials)

Evaluation in Machine Learning (morning)

Pádraig Cunningham (University College Dublin)

Keywords: loss functions, accuracy, precision recall, F-Score, ROC and AUC analysis, aggregation using win-tie-loss analysis, cross validation, leave-one-out validation, Statistical tests for ML evaluation, comparing across domains, evaluation blunders.

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Transfer Learning for Reinforcement Learning Domains (afternoon)

Alessandro Lazaric (INRIA Lille) and Matthew Taylor (University of Southern California)

Keywords: transfer learning in AI and ML, theoretical foundation of transfer in RL, task relatedness, transferred knowledge, fixed state-action variables, multitask learning, inter-task mapping, fully autonomous transfer.

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Graphical Models (morning)

Tiberio Caetano (NICTA)

Keywords: belief propagation and junction trees, maximum-likelihood and maximum-a-posteriori estimation, conditional random fields, Markov random fields, Bayesian Networks, nonparametric modeling.

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