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09/28/2020
Graph Adversarial Networks: Protecting Information against Adversarial Attacks
We study the problem of protecting information when learning with graph ...
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09/30/2019
Towards modular and programmable architecture search
Neural architecture search methods are able to find high performance dee...
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03/05/2018
Recurrent Predictive State Policy Networks
We introduce Recurrent Predictive State Policy (RPSP) networks, a recurr...
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12/06/2017
Learning General Latent-Variable Graphical Models with Predictive Belief Propagation and Hilbert Space Embeddings
In this paper, we propose a new algorithm for learning general latent-va...
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05/25/2017
Predictive State Recurrent Neural Networks
We present a new model, Predictive State Recurrent Neural Networks (PSRN...
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02/14/2017
Practical Learning of Predictive State Representations
Over the past decade there has been considerable interest in spectral al...
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05/20/2015
Supervised Learning for Dynamical System Learning
Recently there has been substantial interest in spectral methods for lea...
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09/26/2013
Hilbert Space Embeddings of Predictive State Representations
Predictive State Representations (PSRs) are an expressive class of model...
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12/12/2012
Distributed Planning in Hierarchical Factored MDPs
We present a principled and efficient planning algorithm for collaborati...
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10/19/2012
Decentralized Sensor Fusion With Distributed Particle Filters
This paper presents a scalable Bayesian technique for decentralized stat...
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10/19/2012
Policy-contingent abstraction for robust robot control
This paper presents a scalable control algorithm that enables a deployed...
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05/09/2012
First-Order Mixed Integer Linear Programming
Mixed integer linear programming (MILP) is a powerful representation oft...
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03/15/2012
