The 32nd Uncertainty in Artificial Intelligence Conference: Preface

Alexander Ihler, Dominik Janzing
Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, PMLR R14:1-7, 2016.

Abstract

v Organizing Committee vii Acknowledgments ix Sponsors xvii Best Paper Awards xix 1 Proceedings 1 Gradient Methods for Stackelberg Games. Kareem Amin, Michael Wellman, Satinder Singh . . . . . . . . . . . . . . . . . . . . . . . 1 Inferring Causal Direction from Relational Data. David Arbour, Katerina Marazopoulou, David Jensen . . . . . . . . . . . . . . . . . . . . 12 Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes. Mohamm Gheshlaghi Azar, Eva Dyer, Konrad Kording . . . . . . . . . . . . . . . . . . . 22 The Mondrian Kernel. Matej Balog, Balaji Lakshminarayanan, Zoubin Ghahramani, Daniel Roy, Yee Whye Teh 32 Sequential Nonparametric Testing with the Law of the Iterated Logarithm. Akshay Balsubramani, Aaditya Ramdas . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Budget Allocation using Weakly Coupled, Constrained Markov Decision Processes. Craig Boutilier, Tyler Lu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Analysis of Nystr\"{}om method with sequential ridge leverage scores. Daniele Calandriello, Alessandro Lazaric, Michal Valko . . . . . . . . . . . . . . . . . . . 62 Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data. Krzysztof Chalupka, Tobias Bischoff, Frederick Eberhardt, Pietro Perona . . . . . . . . . . 72 Individual Planning in Open and Typed Agent Systems. Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, Leenkiat Soh . . . . . . . . 82 Modeling Transitivity in Complex Networks. Morteza Haghir Chehreghani, Mostafa Haghir Chehreghani . . . . . . . . . . . . . . . . . 92 Adversarial Inverse Optimal Control for General Imitation Learning Losses and Embodiment Transfer. Xiangli Chen, Mathew Monfort, Brian Ziebart, Peter Carr . . . . . . . . . . . . . . . . . 102 A Generative Block-Diagonal Model for Clustering. Junxiang Chen, Jennifer Dy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections. Jianhui Chen, Tianbao Yang, Qihang Lin, Lijun Zhang, Yi Chang . . . . . . . . . . . . . 122 Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization. Jinghui Chen, Quanquan Gu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Online Bayesian Multiple Kernel Bipartite Ranking. Changying Du, Changde Du, Guoping Long, Qing He, Yucheng Li . . . . . .

Cite this Paper

BibTeX
@InProceedings{pmlr-vR14-ihler16a, title = {The 32nd Uncertainty in Artificial Intelligence Conference: Preface}, author = {Ihler, Alexander and Janzing, Dominik}, booktitle = {Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence}, pages = {1--7}, year = {2016}, editor = {Ihler, Alexander and Janzing, Dominik}, volume = {R14}, series = {Proceedings of Machine Learning Research}, month = {25--29 Jun}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/r14/main/assets/ihler16a/ihler16a.pdf}, url = {https://proceedings.mlr.press/r14/ihler16a.html}, abstract = {v Organizing Committee vii Acknowledgments ix Sponsors xvii Best Paper Awards xix 1 Proceedings 1 Gradient Methods for Stackelberg Games. Kareem Amin, Michael Wellman, Satinder Singh . . . . . . . . . . . . . . . . . . . . . . . 1 Inferring Causal Direction from Relational Data. David Arbour, Katerina Marazopoulou, David Jensen . . . . . . . . . . . . . . . . . . . . 12 Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes. Mohamm Gheshlaghi Azar, Eva Dyer, Konrad Kording . . . . . . . . . . . . . . . . . . . 22 The Mondrian Kernel. Matej Balog, Balaji Lakshminarayanan, Zoubin Ghahramani, Daniel Roy, Yee Whye Teh 32 Sequential Nonparametric Testing with the Law of the Iterated Logarithm. Akshay Balsubramani, Aaditya Ramdas . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Budget Allocation using Weakly Coupled, Constrained Markov Decision Processes. Craig Boutilier, Tyler Lu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Analysis of Nystr\"{}om method with sequential ridge leverage scores. Daniele Calandriello, Alessandro Lazaric, Michal Valko . . . . . . . . . . . . . . . . . . . 62 Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data. Krzysztof Chalupka, Tobias Bischoff, Frederick Eberhardt, Pietro Perona . . . . . . . . . . 72 Individual Planning in Open and Typed Agent Systems. Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, Leenkiat Soh . . . . . . . . 82 Modeling Transitivity in Complex Networks. Morteza Haghir Chehreghani, Mostafa Haghir Chehreghani . . . . . . . . . . . . . . . . . 92 Adversarial Inverse Optimal Control for General Imitation Learning Losses and Embodiment Transfer. Xiangli Chen, Mathew Monfort, Brian Ziebart, Peter Carr . . . . . . . . . . . . . . . . . 102 A Generative Block-Diagonal Model for Clustering. Junxiang Chen, Jennifer Dy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections. Jianhui Chen, Tianbao Yang, Qihang Lin, Lijun Zhang, Yi Chang . . . . . . . . . . . . . 122 Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization. Jinghui Chen, Quanquan Gu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Online Bayesian Multiple Kernel Bipartite Ranking. Changying Du, Changde Du, Guoping Long, Qing He, Yucheng Li . . . . . .}, note = {Reissued by PMLR on 04 October 2026.} }
Endnote
%0 Conference Paper %T The 32nd Uncertainty in Artificial Intelligence Conference: Preface %A Alexander Ihler %A Dominik Janzing %B Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence %C Proceedings of Machine Learning Research %D 2016 %E Alexander Ihler %E Dominik Janzing %F pmlr-vR14-ihler16a %I PMLR %P 1--7 %U https://proceedings.mlr.press/r14/ihler16a.html %V R14 %X v Organizing Committee vii Acknowledgments ix Sponsors xvii Best Paper Awards xix 1 Proceedings 1 Gradient Methods for Stackelberg Games. Kareem Amin, Michael Wellman, Satinder Singh . . . . . . . . . . . . . . . . . . . . . . . 1 Inferring Causal Direction from Relational Data. David Arbour, Katerina Marazopoulou, David Jensen . . . . . . . . . . . . . . . . . . . . 12 Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes. Mohamm Gheshlaghi Azar, Eva Dyer, Konrad Kording . . . . . . . . . . . . . . . . . . . 22 The Mondrian Kernel. Matej Balog, Balaji Lakshminarayanan, Zoubin Ghahramani, Daniel Roy, Yee Whye Teh 32 Sequential Nonparametric Testing with the Law of the Iterated Logarithm. Akshay Balsubramani, Aaditya Ramdas . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Budget Allocation using Weakly Coupled, Constrained Markov Decision Processes. Craig Boutilier, Tyler Lu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Analysis of Nystr\"{}om method with sequential ridge leverage scores. Daniele Calandriello, Alessandro Lazaric, Michal Valko . . . . . . . . . . . . . . . . . . . 62 Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data. Krzysztof Chalupka, Tobias Bischoff, Frederick Eberhardt, Pietro Perona . . . . . . . . . . 72 Individual Planning in Open and Typed Agent Systems. Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, Leenkiat Soh . . . . . . . . 82 Modeling Transitivity in Complex Networks. Morteza Haghir Chehreghani, Mostafa Haghir Chehreghani . . . . . . . . . . . . . . . . . 92 Adversarial Inverse Optimal Control for General Imitation Learning Losses and Embodiment Transfer. Xiangli Chen, Mathew Monfort, Brian Ziebart, Peter Carr . . . . . . . . . . . . . . . . . 102 A Generative Block-Diagonal Model for Clustering. Junxiang Chen, Jennifer Dy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections. Jianhui Chen, Tianbao Yang, Qihang Lin, Lijun Zhang, Yi Chang . . . . . . . . . . . . . 122 Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization. Jinghui Chen, Quanquan Gu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Online Bayesian Multiple Kernel Bipartite Ranking. Changying Du, Changde Du, Guoping Long, Qing He, Yucheng Li . . . . . . %Z Reissued by PMLR on 04 October 2026.
APA
Ihler, A. & Janzing, D.. (2016). The 32nd Uncertainty in Artificial Intelligence Conference: Preface. Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence, in Proceedings of Machine Learning Research R14:1-7 Available from https://proceedings.mlr.press/r14/ihler16a.html. Reissued by PMLR on 04 October 2026.

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