Research Seminar

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Spring Semester 2024

Date / Time Speaker Title Location
7 March 2024
16:15-17:15
Elliot Young
The University of Cambridge
Event Details

Research Seminar in Statistics

Title Sandwich Boosting for accurate estimation in partially linear models for grouped data
Speaker, Affiliation Elliot Young, The University of Cambridge
Date, Time 7 March 2024, 16:15-17:15
Location HG G 19.1
Abstract We study partially linear models in settings where observations are arranged in independent groups but may exhibit within-group dependence. Existing approaches estimate linear model parameters through weighted least squares, with optimal weights (given by the inverse covariance of the response, conditional on the covariates) typically estimated by maximising a (restricted) likelihood from random effects modelling or by using generalised estimating equations. We introduce a new ‘sandwich loss’ whose population minimiser coincides with the weights of these approaches when the parametric forms for the conditional covariance are well-specified, but can yield arbitrarily large improvements in linear parameter estimation accuracy when they are not. Under relatively mild conditions, our weighted least squares (within a double machine learning framework) estimated coefficients are asymptotically Gaussian and enjoy minimal variance among estimators with weights restricted to a given class of functions, when user-chosen regression methods are used to estimate nuisance functions. We further expand the class of functional forms for the weights that may be fitted beyond parametric models by leveraging the flexibility of modern machine learning methods within a new gradient boosting scheme for minimising the sandwich loss. We demonstrate the effectiveness of both the sandwich loss and what we call ‘sandwich boosting’ in a variety of settings with simulated and real-world data.
Sandwich Boosting for accurate estimation in partially linear models for grouped dataread_more
HG G 19.1
21 March 2024
16:15-17:15
Bryon Aragam
The University of Chicago Booth School of Business
Event Details

Research Seminar in Statistics

Title Research Seminar on Statistics - FDS Seminar joint talk: Statistical aspects of nonparametric latent variable models and causal representation learning
Speaker, Affiliation Bryon Aragam, The University of Chicago Booth School of Business
Date, Time 21 March 2024, 16:15-17:15
Location HG D 1.2
Abstract One of the key paradigm shifts in statistical machine learning over the past decade has been the transition from handcrafted features to automated, data-driven representation learning. A crucial step in this pipeline is to identify latent representations from observational data along with their causal structure. In many applications, the causal variables are not directly observed, and must be learned from data, often using flexible, nonparametric models such as deep neural networks. These settings present new statistical and computational challenges that will be focus of this talk. We will re-visit the statistical foundations of nonparametric latent variable models as a lens into the problem of causal representation learning. We discuss our recent work on developing methods for identifying and learning causal representations from data with rigourous guarantees, and discuss how even basic statistical properties are surprisingly subtle. Along the way, we will explore the connections between causal graphical models, deep generative models, and nonparametric mixture models, and how these connections lead to a useful new theory for causal representation learning.
Research Seminar on Statistics - FDS Seminar joint talk: Statistical aspects of nonparametric latent variable models and causal representation learningread_more
HG D 1.2
26 April 2024
15:15-16:15
Richard De Veaux
Williams College
Event Details

Research Seminar in Statistics

Title Title T.B.A.
Speaker, Affiliation Richard De Veaux, Williams College
Date, Time 26 April 2024, 15:15-16:15
Location HG G 19.1
Abstract tba
Title T.B.A.read_more
HG G 19.1
16 May 2024
15:15-16:15
Jiwei Zhao
University of Wisconsin–Madison
Event Details

Research Seminar in Statistics

Title Title T.B.A.
Speaker, Affiliation Jiwei Zhao, University of Wisconsin–Madison
Date, Time 16 May 2024, 15:15-16:15
Location HG G 19.1
Abstract tba
Title T.B.A.read_more
HG G 19.1

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