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stat.ML2021★ 5 cited
Spectral risk-based learning using unbounded losses
Matthew J. Holland, El Mehdi Haress
In this work, we consider the setting of learning problems under a wide class of spectral risk (or "L-risk") functions, where a Lipschitz-continuous spectral density is used to fle…
stat.ML2020★ 2 cited
Learning with CVaR-based feedback under potentially heavy tails
Matthew J. Holland, El Mehdi Haress
We study learning algorithms that seek to minimize the conditional value-at-risk (CVaR), when all the learner knows is that the losses incurred may be heavy-tailed. We begin by stu…