Lessons from learning theory for benchmark design

John Langford

doi:10.1117/12.555674

2 September 2004 Lessons from learning theory for benchmark design

John Langford

Proceedings Volume 5427, Algorithms for Synthetic Aperture Radar Imagery XI; (2004) https://doi.org/10.1117/12.555674
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

This discussion/tutorial consists of a few short discussions on the (theoretical) trade-offs of various choices in constructing benchmarks. Most of the results discussed here are "common sense" at high level. However, all of this "common sense" is (to some extent) quantifiable common sense, and occasionally that quantification is useful. These short discussions cover: 1) Prediction Domains & Loss functions, 2) Prediction settings, 3) Assumption Failures.

Citation Download Citation

John Langford "Lessons from learning theory for benchmark design", Proc. SPIE 5427, Algorithms for Synthetic Aperture Radar Imagery XI, (2 September 2004); https://doi.org/10.1117/12.555674

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