1 citations · 2 across the 3 of their papers we have counts for
4 papers
Sampling Multiple Nodes in Large Networks: Beyond Random Walks
Omri Ben-Eliezer, Talya Eden, Joel Oren +1
Sampling random nodes is a fundamental algorithmic primitive in the analysis of massive networks, with many modern graph mining algorithms critically relying on it. We consider the…
SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems
Joel Oren, Chana Ross, Maksym Lefarov +5
We study combinatorial problems with real world applications such as machine scheduling, routing, and assignment. We propose a method that combines Reinforcement Learning (RL) and…
Practical Risk Measures in Reinforcement Learning
Dotan Di Castro, Joel Oren, Shie Mannor
Practical application of Reinforcement Learning (RL) often involves risk considerations. We study a generalized approximation scheme for risk measures, based on Monte-Carlo simulat…
Efficient Sum-Based Hierarchical Smoothing Under \ell_1-Norm
Siavosh Benabbas, Hyun Chul Lee, Joel Oren +1
We introduce a new regression problem which we call the Sum-Based Hierarchical Smoothing problem. Given a directed acyclic graph and a non-negative value, called target value, for…