Statistical Learning
KONG: Kernels for ordered-neighborhood graphs
Moez Draief, Konstantin Kutzkov, Kevin Scaman, Milan Vojnovic
We present novel graph kernels for graphs with node and edge labels that have ordered neighborhoods, i.e. when neighbor nodes followanorder.
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
Dominic Richards, Patrick Rebeschini
Due to the increasingly large size of datasets and high model complexity, direct minimisation of the regularised problem is posing more and morecomputationalchallenges.
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits
Bianca Dumitrascu, Karen Feng, Barbara Engelhardt
Its explicit estimation of the posterior distribution of the contextfeature covariance leads tosubstantial empirical gains overapproximate approaches.
The Many Faces of Optimal Weak-to-Strong Learning
's are real-valued weights depending on the accuracy of h
Cost Effective Active Search
Shali Jiang, Roman Garnett, Benjamin Moseley
Neural Information Processing Systems http://nips.cc/
Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD
PHUONG_HA NGUYEN, Lam Nguyen, Marten van Dijk
Neural Information Processing Systems http://nips.cc/