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Classification using margin pursuit
[article]
2018
arXiv
pre-print
In this work, we study a new approach to optimizing the margin distribution realized by binary classifiers. The classical approach to this problem is simply maximization of the expected margin, while more recent proposals consider simultaneous variance control and proxy objectives based on robust location estimates, in the vein of keeping the margin distribution sharply concentrated in a desirable region. While conceptually appealing, these new approaches are often computationally unwieldy, and
arXiv:1810.04863v1
fatcat:ogxqnmycgjd6tedrugryrs4j3e