160 citations · 1.5k across the 122 of their papers we have counts for
Showing 2018 · stat.MLShow all
3 papers · 2 filters
stat.ML2018★ 1 cited
Online Multiclass Boosting with Bandit Feedback
Daniel T. Zhang, Young Hun Jung, Ambuj Tewari
We present online boosting algorithms for multiclass classification with bandit feedback, where the learner only receives feedback about the correctness of its prediction. We propo…
stat.ML2018
Fighting Contextual Bandits with Stochastic Smoothing
Young Hun Jung, Ambuj Tewari
We introduce a new stochastic smoothing perspective to study adversarial contextual bandit problems. We propose a general algorithm template that represents random perturbation bas…
stat.ML2018★ 16 cited
On the Approximation Properties of Random ReLU Features
Yitong Sun, Anna Gilbert, Ambuj Tewari
We study the approximation properties of random ReLU features through their reproducing kernel Hilbert space (RKHS). We first prove a universality theorem for the RKHS induced by r…