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ANC Workshop Talk: Yichuan Zhang and Richard Shillcock, Chair: David Reichert

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  • ANC Workshop Talk
When Apr 17, 2012
from 11:00 AM to 12:00 PM
Where IF 4.31/4.33
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Yichuan Zhang

Markov chain Monte Carlo (MCMC) methods are powerful tools for inference on state-of-the-art machine learning models. The gradient of probability density function is used in advanced MCMC methods, like Hamiltonian Monte Carlo (HMC). However, only using local gradient usually cannot help the sampler move to the far side of the sampling space when the target distribution is complex. In high-dimensional space, MCMC sampler may also suffer from local random walk. I'm going to talk about my previous work on quasi-Newton Markov chain Monte Carlo. In this work, we found that the performance of HMC methods can be improved by combining multiple gradient at previous samples. I will also talk about my recent work on a new geometric perspective of MCMC methods and how it can be used to draw samples efficiently in high dimensions.


Richard Shillcock

Isolated word recognition: reconciling visual information, visual pathways, hemispheres, sex and relative handedness of the reader

I will discuss new data from a novel haploscopic means of presenting single brief words for identification.  This technique reveals a complex interaction of the visual information structure of the word with the processing implications of the anatomy of the visual pathways and cortex, showing interactions with the visual pathways, the cerebral hemispheres, the sex and the relative handedness of the reader.  These interactions are interpretable in terms of the goodness of the pathways from retina to cortex, the coding preferences of the respective hemispheres, and the relative preference for single-hemisphere over bihemispheric processing.  Reading even a single word emerges as a complex process intimately dependent upon the visual and cortical anatomy of the reader. The critical factor affecting all of these processes is the relative positioning of the fixation points of the right and left eye with respect to the plane of the text.