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 Tue Dec 05, 2017

Time Hall A
10:40 AM (Orals)
Algorithms
Diffusion Approximations for Online Principal Component Estimation and Global Convergence
10:55 AM (Orals)
Positive-Unlabeled Learning with Non-Negative Risk Estimator
11:10 AM (Orals)
Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search
11:25 AM (Spotlights)
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
11:30 AM (Spotlights)
Communication-Efficient Stochastic Gradient Descent, with Applications to Neural Networks
11:35 AM (Spotlights)
Inhomogoenous Hypergraph Clustering with Applications
11:40 AM (Spotlights)
K-Medoids For K-Means Seeding
11:45 AM (Spotlights)
Online Learning with Transductive Regret
11:50 AM (Spotlights)
Matrix Norm Estimation from a Few Entries
11:55 AM (Spotlights)
Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding