339 citations · 1k across the 41 of their papers we have counts for
Showing 2014 · cs.LGShow all
3 papers · 2 filters
cs.LG2014★ 3 cited
Exploiting Smoothness in Statistical Learning, Sequential Prediction, and Stochastic Optimization
Mehrdad Mahdavi
In the last several years, the intimate connection between convex optimization and learning problems, in both statistical and sequential frameworks, has shifted the focus of algori…
cs.LG2014★ 4 cited
Excess Risk Bounds for Exponentially Concave Losses
Mehrdad Mahdavi, Rong Jin
The overarching goal of this paper is to derive excess risk bounds for learning from exp-concave loss functions in passive and sequential learning settings. Exp-concave loss functi…
cs.LG2014★ 4 cited
Binary Excess Risk for Smooth Convex Surrogates
Mehrdad Mahdavi, Lijun Zhang, Rong Jin
In statistical learning theory, convex surrogates of the 0-1 loss are highly preferred because of the computational and theoretical virtues that convexity brings in. This is of mor…