Predictive State Representations / Spectral Learning

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  • Improving Predictive State Representations via Gradient Descent.
    by Nan Jiang, Alex Kulesza, and Satinder Singh.
    In Thirtieth AAAI Conference on Artificial Intelligence (AAAI), 2016.
    pdf.

  • Low-Rank Spectral Learning with Weighted Loss Functions.
    by Alex Kulesza, Nan Jiang, and Satinder Singh.
    In Eighteenth International Conference on Artificial Intelligence and Statistics (AISTATS), 2015.
    pdf.

  • Spectral Learning of Predictive State Representations with Insufficient Statistics.
    by Alex Kulesza, Nan Jiang, and Satinder Singh.
    In Twenty-Ninth AAAI Conference, 2015.
    pdf.

  • Low-Rank Spectral Learning.
    by Alex Kulesza, Nadakuditi Raj Rao, and Satinder Singh.
    In Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS), 2014.
    pdf.

  • Efficiently Learning Linear-Linear Exponential Family Predictive Representations of State
    by David Wingate and Satinder Singh.
    In Proceedings of the 25th International Conference on Machine Learning (ICML), pages 1176-1183, 2008.
    pdf

  • Predictive Linear-Gaussian Models of Stochastic Dynamical Systems with Vector-Value Actions and Observations
    by Matthew Rudary and Satinder Singh.
    In Proceedings of the Tenth International Symposium on Artificial Intelligence and Mathematics (ISAIM), 2008.
    pdf

  • Approximate Predictive State Representations
    by Britton Wolfe, Michael R. James and Satinder Singh.
    In Procedings of the 2008 International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2008.
    (Finalist for Pragnesh Jay Modi Best Student Paper Award)
    pdf

  • On Discovery and Learning of Models with Predictive State Representations of State for Agents with Continuous Actions and Observations
    by David Wingate and Satinder Singh.
    In Procedings of the 2007 International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2007.
    pdf

  • Relational Knowledge with Predictive State Representations
    by David Wingate, Vishal Soni, Britton Wolfe and Satinder Singh.
    In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI), pages 2035-2040, 2007.
    pdf

  • Abstraction in Predictive State Representations
    by Vishal Soni and Satinder Singh.
    In Proceedings of the 22nd National Conference on Artificial Intelligence (AAAI), 2007.
    pdf

  • Exponential Family Predictive Representations of State
    by David Wnigate and Satinder Singh.
    In Proceedings of the Advances in Neural Information Processing Systems, 20 (NIPS), pages 1617-1624, 2007.
    pdf

  • Mixtures of Predictive Linear Gaussian Models for Nonlinear Stochastic Dynamical Systems
    by David Wingate and Satinder Singh.
    In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI), 2006.
    pdf

  • Kernel Predictive Linear-Gaussian Models for Nonlinear Stochastic Dynamical Systems
    by David Wingate and Satinder Singh.
    In Proceedings of the 23rd International Conference on Machine Learning (ICML), pages 1017-1024, 2006.
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  • Predictive linear-Gaussian models of controlled stochastic dynamical systems
    by Matthew Rudary and Satinder Singh.
    In Proceedings of the 23rd International Conference on Machine Learning (ICML), pages 777-784, 2006.
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  • Predictive State Representations with Options
    by Britton Wolfe and Satinder Singh.
    In Proceedings of the 23rd International Conference on Machine Learning (ICML), pages 1025-1032, 2006.
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  • Predictive linear-Gaussian models of stochastic dynamical systems
    by Matthew Rudary, Satinder Singh and David Wingate.
    In Proceedings of the Uncertainty in Artificial Intelligence (UAI), pages 501-508, 2005.
    pdf

  • Combining Memory and Landmarks with Predictive State Representations
    by Michael R. James, Britton Wolfe and Satinder Singh.
    In Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI), 2005.
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  • Planning in Models that Combine Memory with Predictive Representations of State
    by Michael R. James and Satinder Singh.
    In Proceedings of the 20th National Conference on Artificial Intelligence (AAAI), pages 987-992, 2005.
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  • Learning Predictive State Representations in Dynamical Systems Without Reset
    by Britton Wolfe, Michael R. James and Satinder Singh.
    In Proceedings of the 22nd International Conference on Machine Learning (ICML), 2005.
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  • Predictive State Representations: A New Theory for Modeling Dynamical Systems
    by Satinder Singh, Michael R. James and Matthew R. Rudary.
    In Uncertainty in Artificial Intelligence: Proceedings of the Twentieth Conference (UAI), pages 512-519, 2004.
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  • Learning and Discovery of Predictive State Representations in Dynamical Systems with Reset
    by Michael James and Satinder Singh.
    In Proceedings of the Twenty-First International Conference on Machine Learning (ICML), pages 417-424, 2004.
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  • Planning with Predictive State Representations
    by Michael R. James, Satinder Singh and Michael Littman.
    In Proceedings of the International Conference on Machine Learning and Applications (ICMLA), pages 304-311, 2004.
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  • A Nonlinear Predictive State Representation
    by Matthew Rudary and Satinder Singh.
    In Advances in Neural Information Processing Systems 16 (NIPS), pages 855-862, 2004.
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  • Learning Predictive State Representations
    by Satinder Singh, Michael Littman, Nicholas Jong, David Pardoe and Peter Stone.
    In Proceedings of the Twentieth International Conference on Machine Learning (ICML), pages 712-719, 2003.
    pdf

  • Predictive Representations of State
    by Michael Littman, Richard Sutton and Satinder Singh.
    In Advances in Neural Information Processing Systems 14 (NIPS), pages 1555-1561, 2002.
    pdf

    Magazine Articles, Book Chapters and Others

  • An Exploration of Low-Rank Spectral Learning.
    by Alex Kulesza, Nadakuditi Raj Rao, and Satinder Singh.
    In ICML Workshop on Spectral Learning, 2013.
    pdf.