What's new?
[Very outdated! I'm no longer doing search or face recognition, but all sorts of large scale
statistical inference.]
Collaborative filtering
Netflix. The constant challenge. I'm still at it, and
Ole Winther and I
are still Gibbs sampling and constructing mean field approximations.
Blaise Thomson
is in the loop too. See our talk at the NIPS 2007 workshop (link at end
of "Research" page). Now to write it all up...
Free energy and perturbations
Recently, Sudderth, Wainwright and Willsky (Loop Series and Bethe Variational Bounds in Attractive Graphical Models)
showed that belief propagation (Bethe-Peierls free energy) can in certain cases
give a lower bound to a partition function, or, in Bayesian language, a log marginal likelihood.
They used Chertkov and Chernyak's loop expansion to show their result; the bounds were also
much better than standard variational or mean field bounds!
Expectation propagation is belief propagation's bigger brother. When will EP give a bound?
In the "Research" page there is a link to a paper by Manfred Opper, Ole Winther and myself.
We already have a Feynman diagram expansion... This is too interesting. I wish I had more time!
Image similarity search
Very much bobbing around the top of the pile at the moment. Imense now has a nice image similarity search
system, and I can spell "Java" backwards now! Lots of wavelets, and heuristics, and random
projections... There will be a web front-end soon, but in the meantime, we're happy to
demo what we have! It is already being used commercially.
I'm also interested in inverted indexing and search, which brings me to
"Hashing".
Hashing
How do we make retrieval fast and very scalable? How do we design machine learning
methods that run in O(log N) or constant time?
Face recognition and all that
For face recognition in full form, please see the advanced
options in the Imense search engine.
I'm really happy with the results, and as usual Chris Town has done a sterling job of putting
all sorts of probabilities from lots of classifiers into our index.
I was also toying with automatic face clustering and labelling; here is a screenshot:
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