2016 - 2017

2016 Jul 14

Stat Colloq: Fabio Cuzzolin

4:15pm to 5:15pm

Location: 

Science Center Rm. 705

Belief Functions: Past, Present, and Future

The theory of belief functions, sometimes referred to as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, to be later developed by Glenn Shafer as a general framework for modelling epistemic uncertainty. Belief theory and the closely related random set theory form a natural framework for modelling situations in which data are missing or scarce: think of extremely rare events such as volcanic eruptions or power plant meltdowns, problems subject to huge...

Read more about Stat Colloq: Fabio Cuzzolin
2016 Dec 05

Colloq: Edward Glaeser & Nikhil Naik

4:15pm to 5:15pm

Location: 

Science Center Rm. 300H

Visualizing the City

Google Streetview now provides an enormously rich picture of the physical streetscapes of the world's cities. Advances in computer recognition techniques make it possible to use images to predict local demographics or the curb appeal of particular places. We show how the combination of Google Streetview and computer vision techniques can map the patterns of neighborhood in six American cities. We also use these methods to predict income in...

Read more about Colloq: Edward Glaeser & Nikhil Naik
2016 Nov 28

Colloq: Kristian Lum

4:15pm to 5:15pm

Location: 

Science Center Rm. 300H

Bias in, bias out: predictive models in the criminal justice system

Predictive models are increasingly used in the criminal justice system to try to predict who will commit crime in the future and where that crime will occur. But what happens when these models are trained using biased data? In this talk, I will present two examples of how biased data is used in the criminal justice system. In the first example, I will introduce a recently published model used...

Read more about Colloq: Kristian Lum
2016 Nov 29

STAT 300: Natesh Pillai

12:00pm to 1:00pm

Location: 

Science Center Rm. 705
Accelerating MCMC algorithms for computer models
2017 Apr 17

Colloq: Ya Xu

4:15pm to 5:15pm

Location: 

Science Center Hall E
ya_xu
2016 Sep 08

Study Card Day

(All day)

Also known as Course Registration Day.
2016 Oct 24

Colloq: Tracy Ke

4:15pm to 5:15pm

Location: 

Science Center Rm. 300H

Social Networks for Statisticians

We have collected a data set for the social networks of statisticians. The data set consists of the meta information (e.g., authors, abstracts, citation counts) of about 70,000 papers in 36 representative journals in statistics and related fields, from 1984-2015. Our data collection project (which we may call it the Phase II) is a continuation of the recent data collection project by Ji and Jin (which we may call the Phase I)....

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2016 Nov 22

STAT 310: Kaisey Mandel

1:00pm to 2:30pm

Location: 

Science Center Rm. 706

The Type Ia Supernova Color­-Magnitude Relation and Host Galaxy Dust: A Simple Hierarchical Bayesian Model

Type Ia supernovae (SN Ia) are faraway exploding stars used as ``standardizable candles'' to determine cosmological distances, measure the accelerating expansion of the Universe, and constrain the properties of dark energy. Inferring peak luminosities of SN Ia from distance-independent observables, such as the shapes and colors of their light curves (time series), underpins the evidence for cosmic...

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