[iasmath-semru] [math-ias] Information added to Thursday's Seminar on TML

[Kristina Phillips]

INSTITUTE FOR ADVANCED STUDY

School of Mathematics

Princeton, NJ 08540

 

Mathematics Seminars

Thursday, April 12
 
 
Seminar on Theoretical Machine Learning
Topic:                    Stability and Generalization in Adaptive Data
Analysis
Speaker:                 Vitaly Feldman, Google Brain
Time/Room:          12:15pm - 1:45pm/White-Levy Room
Abstract Link:        http://www.math.ias.edu/seminars/abstract?event=135273

Datasets are often used multiple times with each successive analysis
depending on the outcomes of previous analyses on the same dataset. Standard
techniques for ensuring generalization and statistical validity do not
account for this adaptive dependence. In this talk I will overview a recent
line of work on adaptive data analysis that studies the problem of answering
a sequence of "queries" about the data distribution where each query may
depend arbitrarily on answers to previous queries. I'll then focus on a new
notion of algorithmic stability with the important property that it
"composes" well when data is reused. I'll demonstrate that this notion of
stability implies that the algorithm reveals little information about its
input and, in particular, cannot lead to overfitting. Finally, I'll describe
simple algorithms based on this notion that can answer statistical queries
about the dataset with substantially improved accuracy guarantees for
low-variance queries.
 
Based in part on a joint work with Thomas Steinke.

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