[AI Seminar] AI Lunch -- Manzil Zaheer -- March 28

[Adams Wei Yu]

Just a gentle reminder that the talk would be tomorrow (Tuesday) noon.

On Sun, Mar 26, 2017 at 2:04 PM, Adams Wei Yu <weiyu at cs.cmu.edu> wrote:

> Dear faculty and students,
>
> We look forward to seeing you Next Tuesday, March 28, at noon in NSH 3305
> for AI lunch. To learn more about the seminar and lunch, please visit the
> AI Lunch webpage <http://www.cs.cmu.edu/~aiseminar/>.
>
> On Tuesday, Manzil Zaheer <http://manzil.ml/> will give a talk titled
> *Exponential Stochastic Cellular Automata For Massively Parallel Inference*.
>
> *Abstract*:
>
> Often statistical models and inference procedures thereof are directly not
> good fit for the modern computational resources. To elaborate, current
> computational resources are racks of fast, cheap, and heavily multicored
> machines yet with a limited memory bandwidth whereas inference strategies
> can be inherently sequentially like Gibbs sampling or memory access
> intensive like expectation-maximization or other variational inference.
>
> In this talk, we discuss an embarrassingly parallel, memory efficient
> inference algorithm for latent variable models in which the complete data
> likelihood is in the exponential family. The algorithm is a stochastic
> cellular automaton and converges to a valid maximum a posteriori fixed
> point. We explore further tricks to improve performance by reducing
> pressure on memory bandwidth by use of better data structures.
> We apply the algorithm to Gaussian mixture model (GMM) and latent
> Dirichlet allocation (LDA) and empirically find that our algorithm is order
> of magnitudes faster than state-of-the-art approaches. A simple C++/MPI
> implementation on a 16-node cluster can sample more than a billion tokens
> per second in case of LDA and a million images in case of GMM.
>
> This is a joint work with Alex Smola, Jean-Baptiste Tristan, Michael Wick,
> and Satwik Kottur.
>
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