I am currently a graduate student in the Computer Science department at the University of British Columbia, supervised by
Nando de Freitas and Arnaud Doucet. I'm working on
various approaches to reformulate stochastic control problems as inference
problems—particularly in large, continuous domains.
I was previously an undergraduate in the Computer Science department at the University of Washington (I was also known to dabble a little bit in the Math department). While there I worked with Rajesh Rao as a member of the Neural Systems Group—primarily on problems of gaze-imitation and imitation-learning utilizing shared-attention. For further information see the relevant publications.
For more information, take a look at my CV.
Publications
M. Hoffman, H. Kueck, N. de Freitas, A. Doucet. New inference strategies for solving Markov Decision Processes using reversible jump MCMC. UAI, 2009.
H. Kueck, M. Hoffman, A. Doucet, N. de Freitas. Inference and Learning for Active Sensing, Experimental Design, and Control. Invited paper, IBPRIA, 2009.
M. Hoffman, N. de Freitas, A. Doucet, Jan Peters. An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Rewards. AISTATS, 2009. (errata, earlier version)
M. Hoffman, A. Doucet, N. de Freitas, and A. Jasra. Bayesian policy learning with trans-dimensional MCMC. NIPS, 2007. (This is an extended and greatly revised version of UBC CS TR-2007-04.)
M. Hoffman, A. Doucet, N. de Freitas, and A. Jasra. On Solving General State-Space Sequential Decision Problems using Inference Algorithms. UBC CS TR-2007-04. March, 2007.
M. Hoffman, D. Grimes, A. Shon, and R. Rao. A probabilistic model of gaze imitation and shared attention. Neural Networks 19(3): Special Issue on Brain Mechanisms of Imitation; 299-310 (2006).
A. Shon, D. Grimes, C. Baker, M. Hoffman, S. Zhou, R. Rao. Probabilistic gaze imitation and saliency learning in a robotic head. ICRA, 2005.
Teaching
The following links should contain outlines for the tutorials I gave (or am giving) while TAing for each of the respective classes. Caveat lector: the slides/outlines may contain minor errors that I didn't catch (email me if it's something particularly blatant).
- CPSC 121 (intro. to theory); Winter 2006/2; Summer 2006/2.
- CPSC 317 (intro. to computer networking); Summer 2006/1.
Misc.
I have posted various hints/tips/etc here. This basically serves two purposes: to make all of my little scripts available so I can refer people to them, and my real motive—so I don't actually forget all of this stuff.
You can also take a look at some of my bookmarks/links/etc.