SUA4: Eliciting High-Quality Information - Boi Faltings, Goran Radanovic.SUA3: Causal Inference and the Data-Fusion Problem - Elias Barenboim.SUA2: Learning Bayesian Networks for Complex Relational Data - Oliver Schulte, Ted Kirkpatrick.SUA1: Deep Learning Implementations and Frameworks - Seiya Tokui, Kenta Oono, Atsunori Kanemura.SP6: Social Data Bias in Machine Learning: Impact, Evaluation, and Correction - Huan Liu, Fred Morstatter.SP5: AI for Data-Driven Decisions in Water Management - Biplav Srivastava, Sandeep S.SP4: Modeling and Solving AI Problems in Picat - Roman Barták, Neng-Fa Zhou.SP3: AI Planning for Robotics - Michael Cashmore, Daniele Magazzeni.SP2: Statistical Relational Artificial Intelligence: Logic, Probability and Computation - Luc De Raedt, David Poole, Kristian Kersting, Sriraam Natarajan.SP1: Recent Advances in Distributed Machine Learning - Wei Chen, Taifeng Wang, Tie-Yan Liu.SA5: Computer Poker - Sam Ganzfried, Johannes Heinrich, Kevin Waugh.SA4: IoT Big Data Stream Minin - Gianmarco De Francisci Morales, Albert Bifet, Latifur Khan, Joao Gama, Wei Fan.SA3: Rulelog: Deep KRR for Cognitive Computing - Benjamin Grosof, Michael Kifer, Paul Fodor.SA2: Risk-Averse Decision Making and Control - Marek Petrik, Mohammad Ghavamzadeh.SA1: Learn to Write a Scientific Paper of the Future: Reproducible Research, Open Science, and Digital Scholarship - Yolanda Gil, Daniel Garijo, Gail Peretsman-Clement.(except where noted times include breaks, if applicable) (All tutorials are 4 hours, including breaks, unless otherwise noted.)
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