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Experimental Evaluation of Algorithm-Assisted Human Decision-Making: Application to Pretrial Public Safety Assessment

December 14, 2020

Speakers:

Kosuke Imai, Harvard University

Despite an increasing reliance on fully-automated algorithmic decision making in our day-to-day lives, human beings still make highly consequential

Resilience to Online Censorship

December 7, 2020

Speakers:

Margaret E. Roberts, University of California

To what extent are Internet users resilient to online censorship?

Identifying the latent space geometry of network models through analysis of curvature

November 30, 2020

Speakers:

Tyler H. McCormick, University of Washington

Modeling statistical and economic networks is fundamentally challenging because of (often high-order) dependence between connections. A common app

Quasi-Monte Carlo for Multivariate Distributions via Generative Neural Networks

November 26, 2020

Speakers:

Marius Hofert, University of Waterloo

A novel approach based on generative neural networks is introduced for constructing quasi-random number generators for multivariate models with any

School Level Statistics and Data Science: Guided by the Pre-K-12 GAISE II Framework

November 23, 2020

Speakers:

Christine Franklin, Senior Lecturer Emeritus

This presentation highlights the role of questioning in statistics and data science with three examples from the newly revised American Statistical

Rethinking the Role of Optimization in Learning

November 12, 2020

Speakers:

Suriya Gunasekar, Senior Researcher, Microsoft Research at Redmond

In this talk, I will overview recent results towards understanding how we learn large capacity machine learning models.

Bayesian Canonicalization of Voter Registration Files

November 5, 2020

Speakers:

Andee Kaplan, Colorado State University

Entity resolution (record linkage or de-deduplication) is the process of merging noisy databases to remove duplicate entities in the absence of a u

The art and science of teaching data science

November 2, 2020

Speakers:

Mine Çetinkaya-Rundel

Modern statistics is fundamentally a computational discipline, but too often this fact is not reflected in our statistics curricula.

Highly Scalable Gaussian Processes for Spatial Data Analysis

October 29, 2020

Speakers:

Sudipto Banerjee, UCLA

The BIG DATA problem in multivariate geostatistics has fomented a rich literature on scalable methodologies for analysing massive multivariate spat

Fairness, Accountability, and Transparency: (Counter)-Examples from Predictive Models in Criminal Justice

October 26, 2020

Speakers:

Kristian Lum, University of Pennsylvania

The need for fairness, accountability, and transparency in computer models that make or inform decisions about people has become increasingly clear

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