• Click on the titles of individual talks for abstract, slides and archived video (if applicable).

All events take place in the Calvin Lab Auditorium.

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Coffee and Check-In
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Opening Remarks
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Machine Learning from Verbal User Instruction
Tom Mitchell, Carnegie Mellon University
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Break
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Machine Teaching in Interactive Learning
Jerry Zhu, University of Wisconsin-Madison
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Lunch
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Interactively Learning Robot Objective Functions
Anca Dragan, UC Berkeley
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Words, Pictures, and Common Sense
Devi Parikh, Georgia Institute of Technology
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Break
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Stochastic Variance Reduction Methods for Policy Evaluation
Lihong Li, Microsoft Research
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Discussion
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Reception
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Coffee and Check-In
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Interactive Clustering
Pranjal Awasthi, Rutgers University
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Break
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Crowdsourcing and Machine Learning
Adam Kalai, Microsoft Research New England
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Lunch
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Active Learning Beyond Label Feedback
Kamalika Chaudhuri, UC San Diego
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Active Learning for Multidimensional Experimental Spaces of Biological Responses
Robert Murphy, Carnegie Mellon University
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Break
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Interactive Language Learning from the Extremes
Sida Wang, Stanford University
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Discussion
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Coffee and Check-In
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Robot Learning from Motor-Impaired Teachers and Task Partners
Brenna Argall, Northwestern University
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Break
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Sample-Efficient Reinforcement Learning with Rich Observations
Alekh Agarwal, Microsoft Research New York
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Lunch
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Robots Learning from Human Interactions
Andrea Thomaz, University of Texas at Austin
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Robot Learning, Interaction and Reliable Autonomy
Sonia Chernova, Georgia Institute of Technology
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Break
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Interactive Learning of Parsers from Weak Supervision
Luke Zettlemoyer, University of Washington
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Discussion
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Coffee and Check-In
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Power of Active Sampling for Unsupervised Learning
Aarti Singh, Carnegie Mellon University
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Break
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Leveraging Union of Subspace Structure to Improve Constrained Clustering
L, aura Balzano, University of Michigan
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Lunch
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Corralling a Band of Bandit Algorithms
Haipeng Luo, Microsoft Research
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The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits
Csaba Szepesvari, University of Alberta
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RL of Partially Observable Environments Using Spectral Methods
Kamyar Azizzadenesheli, UC Irvine
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Safety in Exploration
Andreas Krause, ETH Zurich
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Optimizing the Spec in RL
Emma Brunskill, Carnegie Mellon University
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Break
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I-SED: An Interactive Sound Event Detector
Bongjun Kim, Northwestern University
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Data Dependent Hierarchical Interactive Classification Learning
Shai Ben-David (University of Waterloo and Vector Institute )
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Learning with Feature Feedback: From Theory to Practice
Stefanos Poulis, UC San Diego
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Active Nearest Neighbors in Changing Environments
Ruth Urner, Max Planck Institute for Intelligent Systems, Tuebingen
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Interactive Learning Opportunities for the Air Force
Lee Seversky, Air Force Research Laboratory
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Coffee and Check-In
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Hierarchical Learning for Human-Robot Collaboration
Brian Scassellati, Yale University
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Active Nearest-Neighbor Learning in Metric Spaces
Sivan Sabato, Ben Gurion University
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Break
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Systems Presentation
Alekh Agarwal, Microsoft Research New York, Lalit Jain, University of Michigan
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Lunch
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TicToc: A General Technique for Near-Optimal Active Learning with Noise
Steve Hanneke
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Interactive Learning of Mixtures of Submodular Functions
Jeff Bilmes, University of Washington