Alex Smola, Amazon – “Title: Sequence Modeling: From Spectral Methods and Bayesian Nonparametrics to Deep Learning”

When:
September 21, 2017 @ 10:45 am – 12:00 pm
2017-09-21T10:45:00-04:00
2017-09-21T12:00:00-04:00

Location

Hackerman Hall, B-17

Abstract

In this talk I will summarize a few recent developments in the design and analysis of sequence models. Starting with simple parametric models such as HMMs for sequences we look at nonparametric extensions in terms of their ability to model more fine-grained types of state and transition behavior. In particular we consider spectral embeddings, nonparametric Bayesian models such as the nested Chinese Restaurant Franchise and the Dirichlet-Hawkes Process. We conclude with a discussion of deep sequence models for user return time modeling, time-dependent collaborative filtering, and large-vocabulary user profiling.

Host

Vova Braverman

Video

Watch seminar video.

Back to top