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 Tue Dec 05, 2017

Time Hall C
04:20 PM (Orals)
Algorithms
A Linear-Time Kernel Goodness-of-Fit Test
04:35 PM (Orals)
Generalization Properties of Learning with Random Features
04:50 PM (Orals)
Communication-Efficient Distributed Learning of Discrete Distributions
05:05 PM (Spotlights)
Posterior sampling for reinforcement learning: worst-case regret bounds
05:10 PM (Spotlights)
Regret Analysis for Continuous Dueling Bandit
05:15 PM (Spotlights)
Minimal Exploration in Structured Stochastic Bandits
05:20 PM (Spotlights)
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe
05:25 PM (Spotlights)
Diving into the shallows: a computational perspective on large-scale shallow learning
05:30 PM (Spotlights)
Monte-Carlo Tree Search by Best Arm Identification
05:35 PM (Spotlights)
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control
05:40 PM (Spotlights)
Parameter-Free Online Learning via Model Selection
05:45 PM (Spotlights)
Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction
05:50 PM (Spotlights)
Gaussian Quadrature for Kernel Features
05:55 PM (Spotlights)
Online Learning of Linear Dynamical Systems