4 citations · 4 across the 1 of their papers we have counts for
3 papers
stat.ML2020
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning
Aodong Li, Alex Boyd, Padhraic Smyth +1
We consider the problem of online learning in the presence of distribution shifts that occur at an unknown rate and of unknown intensity. We derive a new Bayesian online inference…
stat.ML2020★ 4 cited
User-Dependent Neural Sequence Models for Continuous-Time Event Data
Alex Boyd, Robert Bamler, Stephan Mandt +1
Continuous-time event data are common in applications such as individual behavior data, financial transactions, and medical health records. Modeling such data can be very challengi…
cs.CL2020
Large Scale Multi-Actor Generative Dialog Modeling
Alex Boyd, Raul Puri, Mohammad Shoeybi +2
Non-goal oriented dialog agents (i.e. chatbots) aim to produce varying and engaging conversations with a user; however, they typically exhibit either inconsistent personality acros…