SCIENTIFIC PROGRAMS AND ACTIVITIES

November 19, 2017

THE FIELDS INSTITUTE FOR RESEARCH IN MATHEMATICAL SCIENCES

Thematic Program on Statistical Inference, Learning, and Models for Big Data, January to June, 2015

January 12 – 23, 2015
Opening Conference and Boot Camp
Organizing Committee Location
Nancy Reid (Toronto), Sallie Keller (Virginia Tech),
Lisa Lix (Manitoba), Bin Yu ( UC, Berkeley)
Room 230, Fields Institute

Program

The goals are to to prepare students, postdoctoral fellows, visitors and interested researchers to benefit from the activities to follow, and to build momentum and generate widespread interest in the thematic program. We are very pleased that Robert Bell, ATT Bell Labs, will open the Conference and that Emmanuel Candes will open Day 2 with a Public Lecture. After two overview days, each day is devoted to one of the themes addressed in more depth during the thematic semester.


WEEK ONE: JANUARY 12 - 16

Monday January 12: Introductory Lectures and Overview

8:00

Coffee and Registration

8:45

Welcome

9:00-9:30

Nancy Reid, University of Toronto

9:30-10:30

Keynote Lecture: Bob Bell, AT&T Labs - Research
Big Data: It's Not the Data

10:30-11:00

Coffee

11:00-12:00

Adam Kalai, Microsoft
Machine learning and crowdsourcing

12:00-2:00

Lunch
2:00-3:00
Hugh Chipman, Acadia University
An overview of Statistical Learning
3:00-3:30

Tea

3:30-4:30

Yulia Gel, University of Waterloo
The Role of Modern Social Media Data in Surveillance and Prediction of Infectious Diseases: from Time Series to Networks
4:30
Cash Bar Reception
Tuesday January 13: Introductory Lectures and Overview

9:30-10:30

Keynote Lecture: Emmanuel Candes, Stanford University
Big Data and the Reproducibility of Scientific Research: What Can Statistics Offer

(video)

10:30-11:00

Coffee break

11:00-12:00

Steve Scott, Google Inc
Bayes and Big Data: The Consensus Monte Carlo Algorithm

12:00-1:30

Lunch break

1:30-2:30

Naomi Altman, The Pennsylvania State University
Generalizing Principal Components Analysis

2:30-3:00

Tea break
3:00-4:00
Emmanuel Candes, Stanford University
Randomized Matrix Computations in the Big Data World
Wednesday January 14: Inference

9:30-10:30
Mark Girolami, University of Warwick
Differential Geometric Simulation Methods for Uncertainty Quantification in Large Scale PDE Systems

10:30-11:00

Coffee break

11:00-12:00

Han Liu, Princeton University (presented by Ethan X. Fang, Princeton University)
Testing and Confidence Intervals for High Dimensional Proportional Hazards Model

12:00-2:00

Lunch break

2:00-3:00

Ejaz Ahmed, Brock University
Big Data Analysis: The Universe is not Sparse

3:00-3:30

Tea break
3:30-4:30
Richard Lockhart, Simon Fraser University
Inference after LASSO -- limits and limitations
Thursday January 15: Environmental Science

9:30-10:30

Charmaine Dean, Western University
Wildfire and Forest Disease Prediction to Inform Forest Management: Statistical Science Challenges

10:30-11:00

Coffee break

11:00-12:00

Doug Woolford, Wilfrid Laurier University
Exploratory data analysis, visualization and modelling methods for large data in forest fire science

12:00-2:00

Lunch

2:00-3:00

Bo Li, University of Illinois
Reconstructing Past Temperatures using Short- and Long-memory Models

3:00-3:30

Tea break
3:30-4:30
Alex Schmidt, Universidade Federal do Rio de Janeiro
An overview of covariance structures for spatial and spatio-temporal processes
Friday January 16: Optimization

9:30-10:30

Martin Wainwright, University of California, Berkeley
Statistics meets optimization: Rigorous guarantees for solving nonconvex programs

10:30-11:00

Coffee break

11:00-12:00

Anima Anundkumar, University of California, Irvine
Guaranteed Non-Convex Optimization for Big Data

12:00-2:00

Lunch

2:00-3:00

Stephen Vavasis, University of Waterloo
Clique and Biclique: An example of using convex optimization for data mining

3:00-3:30

Tea break

WEEK TWO: JANUARY 19 - 23

Monday January 19: Visualization

9:30-10:30

Sheelagh Carpendale, University of Calgary
Information Visualization: Making Data Accessible

10:30-11:00

Coffee

11:00-12:00

Dianne Cook, Iowa State University
Data Visualization and Statistical Graphics in Big Data Analysis

12:00-2:00

Lunch
Tuesday January 20: Social Policy

9:00
James Stafford, University of Toronto
Patrick Brown, Cancer Care Ontario

10:30-11:00

Coffee break

11:00-12:00

Chad Gaffield, University of Ottawa
Big Data vs. Human Complexity: An early status report on the central question of the 21st century

12:00-2:00

Lunch break

2:00-3:00

Sallie Keller, Virginia Tech
Building Resilient Cities: Harnessing the Power of Urban Analytics

3:00-3:30

Tea break
3:30-4:30
Shane Reese, Brigham Young University
From Basis Expansions to Insurgency Prediction: Applications of Bayesian Compressive Sensing
Wednesday January 21: Health Policy

9:30-10:30

David Buckeridge, McGill University
Using (Big) Data to Address Challenges in Public Health

10:30-11:00

Coffee break

11:00-12:00

David Henry, Health Systems Data IHPME and Dalla Lana School of Public Health, University of Toronto

12:00-2:00

Lunch break

2:00-3:00

Lisa Lix, University of Manitoba
Chronic Disease Research and Surveillance: The Power of Big Databases, the Challenges of Data Quality

3:00-3:30

Tea break
3:30-4:30
Thérèse Stukel, Institute for Clinical Evaluative Sciences
Innovative uses of big data for health policy research
Thursday January 22: Deep Learning

10:30-11:00

Coffee break

11:00-12:00

Dale Schuurmans, University of Alberta
Convex Methods for Latent Representation Learning

12:00-2:00

Lunch

2:00-3:00

Russ Salakhutdinov, University of Toronto
Learning Structured, Robust, and Multimodal Models

3:00-3:30

Tea break
3:30-4:30
Sham Kakade, Microsoft Research
Non-convex approaches to learning representations
Friday January 23: Networks and Machine Learning

9:30-10:30

Sofia Olhede, University College London
Understanding Large Networks

10:30-11:00

Coffee break

11:00-12:00

Patrick Wolfe, University College London
Estimating Latent Variable Densities for Exchangeable Network Models

12:00-2:00

Lunch

2:00-3:00

Eric Kolaczyk, Boston University
A Whirlwind Tour of Statistical Analysis of Network Data

3:00-3:30

Tea break