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Research interests:I am working on theoretical foundations for machine learning and AI, in particular for reinforcement learning. Below follows some of my peer-reviewed publications: Conc. and Conf. for Discrete Bayesian Seq. Predictors, T. Lattimore, M. Hutter and P. Sunehag ALT'2013 The Sample-Complexity of General RL, T. Lattimore, M. Hutter and P. Sunehag ICML'2013 Online Feature Selection for Brain Computer Interfaces, G. Oliver,P. Sunehag,T. Gedeon CCMB'2013
Reinforcement Learning Agent with Evolving Hypothesis Classes, P. Sunehag, M. Hutter, AGI'2013 Optimistic AIXI, P. Sunehag, M. Hutter, AGI'2012 On ensemble methods for AIXI approximation, J. Veness, P. Sunehag, M. Hutter, AGI'2012 Optimistic Agents are Asymptotically Optimal, P. Sunehag, M. Hutter AusAI'2012 Coding of Non-Stationary Sources ..., P. Sunehag, W. Shao, M. Hutter AusDM'2012 Feature RL using Looping Suffix Trees, M. Daswani, P. Sunehag, M. Hutter EWRL'2012 Context Tree Maximizing Reinforcement Learning, P. Nguyen, P. Sunehag, M. Hutter, AAAI'2012
Asynchronous BCI Using Hidden Semi-Markov Models, G. Oliver, P. Sunehag, T. Gedeon, EMBC'2012 Recursive Channel Selection Techniques for BCI, G. Oliver, P. Sunehag, T. Gedeon, EMBC'2012 Adaptive Context Tree Weighting, A. O'Neill, M. Hutter, W. Shao, P. Sunehag, DCC'2012 Principles of Solomonoff Induction and AIXI, P. Sunehag, M. Hutter Solomonoff Memorial 2011 (Non)Equivalence of Universal Priors, I. Wood.,P. Sunehag, M. Hutter Solomonoff Memorial 2011 Axioms for Rational Reinforcement Learning, P. Sunehag, M. Hutter ALT'2011 Loss functions for improved on-policy control, M. Robards, P. Sunehag, Proc. of EWRL'2011 Feature Reinforcement Learning in Practice, P. Nguyen, P. Sunehag, M. Hutter, Proc. of EWRL'2011 Sparse Kernel-SARSA with an Elig. Trace, M. Robards, P. Sunehag, S. Sanner, B. Marthi ECML'2011 Consistency of Feature Markov Processes P. Sunehag, M. Hutter ALT'2010 Wearable-sensor activity analysis using semi-Markov models with a grammar O. Thomas, P. Sunehag, G. Dror et al. Pervasive and Mobile Computing 6(3): 342-350, 2010 Semi-markov kmeans clustering and activity recognition from ... M. Robards and P. Sunehag ICDM'2009 Variable Metrics Stochastic Approximation Theory P. Sunehag J. Trumpf, S.V.N. Vishwanathan and N. Schraudolph AISTATS'2009 Real method of interpolation on subcouples of codimension one (with S. Astashkin) Studia Math. 185 (2008), 151-168 Using two-stage word frequency models ... P. Sunehag AISTATS'2007 Induced Graph Semantics: Another ... Hammersley-Clifford Thm T. Sears and P. Sunehag MaxEnt'2007 The real interpolation method on couples of intersections (with S. Astashkin) Functional Analysis and Its Applications 40 (2006) 218-221 ... Interpolation of operators that almost agree P. Sunehag Journal of Approx. Th. 130 (2004) 78-98 Interpolation Of Banach Algebras And Tensor Products Of Banach Couples (with S. Kaijser) Journal of Mathematical Analysis and Applications 278 (2003) 367-375 Interpolation of Banach algebras and the unit problem. (with S. Kaijser) In: Function Spaces, Interpolation Theory and Related Topics, de Gruyter, Berlin (2002) 345-354. | |||||||||||||||||
Bio:I did my Ph.D. in theoretical mathematics at Uppsala University in Sweden. The topic of the thesis was interpolation of Banach spaces and Banach Algebras. I then worked at NICTA in Canberra Australia as a machine learning researcher. I worked with Document Analysis, Optimization and activity recognition from body-worn sensor. I joined the ANU as a research fellow in July 2009 where I am primarily working on reinforcement learning, particularly on generic reinforcement learning. | |||||||||||||||||
Research opportunities with Dr Peter SUNEHAG | |||||||||||||||||
Research School of Computer Science
ANU College of Engineering & Computer Science
