no code implementations • NeurIPS 2016 • Oren Anava, Kfir. Y. Levy
The weighted k-nearest neighbors algorithm is one of the most fundamental non-parametric methods in pattern recognition and machine learning.
no code implementations • NeurIPS 2016 • Zohar S. Karnin, Oren Anava
Our main result is a regret guarantee that scales with the variation parameter of the environment, without requiring any prior knowledge about it whatsoever.
no code implementations • NeurIPS 2015 • Oren Anava, Elad Hazan, Shie Mannor
In this work we extend the notion of learning with memory to the general Online Convex Optimization (OCO) framework, and present two algorithms that attain low regret.
no code implementations • 10 Jun 2014 • Oren Anava, Shahar Golan, Nadav Golbandi, Zohar Karnin, Ronny Lempel, Oleg Rokhlenko, Oren Somekh
It is well known that collaborative filtering (CF) based recommender systems provide better modeling of users and items associated with considerable rating history.
no code implementations • 27 Feb 2013 • Oren Anava, Elad Hazan, Shie Mannor
The framework of online learning with memory naturally captures learning problems with temporal constraints, and was previously studied for the experts setting.