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

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Coffee and Check-In
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Opening Remarks
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Unifying Logic and Probability: The BLOG Language
Stuart Russell, UC Berkeley
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Model Checking and Strategy Synthesis for Stochastic Games: From Theory to Practice
Marta Kwiatkowska, University of Oxford
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Break
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Computing Probabilistic Bisimilarity Distances via Policy Iteration
Franck van Breugel, York University
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Lunch
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Quantitative Algebraic Reasoning
Radu Mardare, Aalborg University
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Discussant Session - Franck van Breugel
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Controlling Probabilistic Systems Under Partial Observation
Nathalie Bertrand, INRIA
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Break
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Three Problems in Computable Probability Theory
Cameron Freer, Gamalon Labs
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Discussant Session - Andreas Blass
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Reception
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Coffee and Check-In
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Brief Tutorial on Probabilistic Databases
Dan Suciu, University of Washington
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A Dichotomy for Queries with Negation in Probabilistic Databases
Dan Olteanu, University of Oxford
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Break
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Fourier Representations in Probabilistic Inference
Bart Selman, Cornell University
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Approximate Lifted Inference with Probabilistic Databases
Wolfgang Gatterbauer, Carnegie Mellon University
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Lunch
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Scalable Collective Inference from Richly Structured Data using Probabilistic Soft Logic (PSL)
Lise Getoor, UC Santa Cruz
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Discussant Session - Dan Suciu
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Stochastic Control via Entropy Compression
Dimitris Achlioptas, UC Santa Cruz
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Break
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Probabilistic Reasoning by First-Order Model Counting
Guy Van den Broeck, UCLA
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Discussant Session - Dan Olteanu
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Coffee and Check-In
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A Personal Viewpoint on Probabilistic Programming
Daniel Roy, University of Toronto
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Probabilistic Programming for Augmented Intelligence
Vikash Mansinghka, MIT
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Break
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Differential Privacy
Kunal Talwar, Google
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Pufferfish Privacy Mechanisms for Correlated Data
Kamalika Chaudhuri, UC San Diego
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Lunch
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Axioms for Information Leakage
Catuscia Palamidessi, INRIA - Saclay
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Discussant Session - Radu Mardare
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Constrained Sampling and Counting
Moshe Vardi, Rice University
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Break
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Model Theory of Exchangeable Structures
Rehana Patel, Olin College
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Coffee and Check-In
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Learning about Auctions
Avrim Blum, Carnegie Mellon University
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Random Projections for Probabilistic Inference
Stefano Ermon, Stanford University
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Break
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Outposts Between Average- and Worst-Case Analysis: A Case Study in Auction Design
Tim Roughgarden, Stanford University
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Approximation Algorithms for Optimization under Uncertainty
Anupam Gupta, Carnegie Mellon University
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Lunch
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Semantic Foundations for Probabilistic Programming
Chris Heunen, University of Edinburgh
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Discussant Session - Dana Scott
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Black-Box Variational Inference for Probabilistic Programs
Hongseok Yang, University of Oxford
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Break