When: October 5, 2016, 12:30 PM
Location: 3rd Floor Orchard View Room , Discovery Building
Contact: 608-316-4401, email@example.com
Estimating a Separable Random Field from Binary Observations
Stochastic processes with dynamics at multiple time scales are pervasive in science and engineering. In neuroscience experiments, the spiking dynamics of neurons can exhibit variability both within a given trial (fast time scale) and across trials (fast time scale). The behavior of users on social media often exhibits interesting dynamics within a day (fast time scale), as well as dynamics across days of the year (slow time scale).
I propose a separable two-dimensional (2D) random field (RF) model of multiscale stochastic processes whose dynamics a different scales obey a certain separability condition. I term such processes separable multiscale processes (SMPs) and propose efficient algorithms for estimation, inference and optimization in the separable 2D RF model. I demonstrate this model on data collected from neurons in the anterior cingulate cortex (ACC) in an experiment designed to characterize the neural underpinnings on the observational learning of fear in mice.
The weekly SILO seminar series is made possible through the generous support of the 3M Company and its Advanced Technology Group
SILO is a lecture series with speakers from the UW faculty, graduate students or invited researchers that discuss mathematical related topics. The seminars are organized by WID’s Optimization research group.
SILO’s purpose is to provide a forum that helps connect and recruit mathematically-minded graduate students. SILO is a lunch-and-listen format, where speakers present interesting math topics while the audience eats lunch.