Douglas Aberdeen
Doug worked for several years in the field of Reinforcement Learning before joining Google. Within Google he works on Gmail including things like spam detection, but most recently including Priority Inbox.
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The Learning Behind Gmail Priority Inbox
Preview
Ondrey Pacovsky
LCCC : NIPS 2010 Workshop on Learning on Cores, Clusters and Clouds
The War Against Spam: A report from the front line
Brad Taylor
Dan Fingal
NIPS 2007 Workshop on Machine Learning in Adversarial Environments for Computer Security
Preview abstract
Fighting spam is a success story of real-world machine learning. Despite the occasional spam that does reach our inboxes, the overwhelming majority of spam —
and there is a lot of it — is positively identified. At the same time, the rarity with which users feel the need to check their spam box for false positives demonstrates
a high precision of classification. This paper is an overview of Google’s approach to fighting email abuse with machine learning, and a discussion of some lessons learned.
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The Factored Policy-Gradient Planner
Olivier Buffet
Journal of Artificial Intelligence Research (JAIR), vol. 173 (2008), pp. 722-747
Natural Actor-Critic for Road Traffic Optimisation
Silvia Richter
Jin Yu
Advances in Neural Information Processing Systems, The {MIT} Press, Cambridge, MA (2007)
Policy-Gradients for PSRs and POMDPs
Olivier Buffet
Owen Thomas
Proc. 11th Intl. Conf. on Artificial Intelligence and Statistics (AIstats), Society for Artificial Intelligence and Statistics, San Juan, Puerto Rico (2007)
FF+FPG: Guiding a Policy-Gradient Planner
Olivier Buffet
Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling (ICAPS'07), Providence, USA (2007)
Concurrent Probabilistic Temporal Planning with Policy-Gradients
Olivier Buffet
Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling (ICAPS'07), Providence, USA (2007)
Policy-Gradient for Robust Planning
O. Buffet
Proceedings of the ECAI'06 Workshop on Planning, Learning and Monitoring with Uncertainty and Dynamic Worlds (PLMUDW'06) (2006)
Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation
Nicol N. Schraudolph
Jin Yu
Advances in Neural Information Processing Systems, The {MIT} Press, Cambridge, MA (2006), pp. 1185-1192
The Factored Policy Gradient planner (IPC-06 Version)
Policy-Gradient for Robust Planning (French)
O. Buffet
Actes de la conférence francophone sur l'apprentissage automatique (CAp'06) (2006)
Policy-Gradient Methods for Planning
Advances in Neural Information Processing Systems, The {MIT} Press, Cambridge, MA (2006)
Simulation Methods for Uncertain Decision-Theoretic Planning
O. Buffet
Proceedings of the IJCAI 2005 Workshop on Planning and Learning in A Priori Unknown or Dynamic Domains
Robust Planning with (L)RTDP
O. Buffet
Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI'05) (2005)
Planification robuste avec (L)RTDP
O. Buffet
Actes de la conférence francophone sur l'apprentissage automatique (CAp'05) (2005)
A Two-Teams Approach for Robust Probabilistic Temporal Planning
O. Buffet
Proceedings of the ECML'05 workshop on Reinforcement Learning in Non-Stationary Environments (2005)
Prottle: A Probabilistic Temporal Planner
Decision-Theoretic Military Operations Planning
Filtered Reinforcement Learning
Proceedings of the 15th European Conference on Machine Learning, Springer (2004), pp. 27-38
Policy-Gradient Algorithms for Partially Observable Markov Decision Processes
Ph.D. Thesis, The Australian National University (2003)
Scaling Internal-State Policy-Gradient Methods for POMDPs
Jonathan Baxter
Proceedings of the 19th International Conference on Machine Learning, Morgan Kaufmann, Syndey, Australia (2002)
Emmerald: A fast Matrix-Matrix Multiply Using Intel SIMD Technology
Jonathan Baxter
Concurrency and Computation: Practice and Experience, vol. 13 (2001), pp. 103-119
92c /MFlop/s, Ultra-Large-Scale Neural-Network Training on a PIII Cluster
General Matrix-Matrix Multiplication Using SIMD features of the PIII
Jonathan Baxter
Euro-Par 2000: Parallel Processing, Springer-Verlag, Munich, Germany
