[Dmbu-l] Talk by Been Kim from MIT this Friday, 11/7 10:30 am MCS 148
edori at bu.edu
Mon Nov 3 09:31:58 EST 2014
this week Been Kim from MIT will be giving a talk on Bayesian case-based
reasoning. Let me know if you would like to meet with the speaker.
We present the Bayesian Case Model (BCM), a general framework for Bayesian
case-based reasoning (CBR) and prototype classification and clustering.
BCM brings the intuitive power of CBR to a Bayesian generative framework.
The BCM learns prototypes, the ``quintessential" observations that best
represent clusters in a data set, by performing joint inference on cluster
labels, prototypes and important features. Simultaneously, BCM pursues
sparsity by learning subspaces, the sets of features that play important
roles in the characterization of the prototypes. The prototype and
subspace representation provides quantitative benefits in interpretability
while preserving classification accuracy. Human subject experiments
verify statistically significant improvements to participants'
understanding when using explanations produced by BCM, compared to those
given by prior art.
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