Dominique Haughton, Bentley University, Université Paris 1 and Université Toulouse 1, with the Music Analytics Group at Bentley University
This talk will give an overview of projects at the frontier between data analysis and music (“music analytics”) and will present preliminary results of an analysis of the success of Kickstarter rock music projects, using features extracted from audio files with the Echonest/Spotify API (Application Program Interface). We also discuss current state of the art in defining measures of distance...
Recent Advances in Post-Selection Statistical Inference
We describe the problem of “post-selection inference.” This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have “cherry-picked”—searched for the strongest associations—means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very...
Model-free knockoffs: high-dimensional variable selection that controls the false discovery rate
Many contemporary large-scale applications involve building interpretable models linking a large set of potential covariates to a response in a nonlinear fashion, such as when the response is binary. Although this modeling problem has been extensively studied, it remains unclear how to effectively control the fraction of false discoveries even in high-dimensional logistic regression, not to mention general high-dimensional nonlinear models. To address such a practical problem...
In this talk, I will discuss three examples of sparse signal detection problems in the context of binary outcomes. These will be motivated by examples from next generation sequencing association studies, understanding heterogeneities in large scale networks, and exploring opinion distributions over networks. Moreover, these three examples will serve as templates to explore interesting phase transitions present in such studies. In particular, these phase transitions will be aimed at revealing a difference between studies with...
How can one combine a collection of estimators of a regression function into a good aggregate? In the last 15 years, this age-old question has received increasing attention within the Mathematical Statistics community. A closely related question of regression in misspecified models has been studied within Statistical Learning using the techniques of empirical processes. We outline the...
