118 citations · 122 across the 9 of their papers we have counts for
5 papers · 1 filter
CONFIDE: Contextual Finite Differences Modelling of PDEs
Ori Linial, Orly Avner, Dotan Di Castro
We introduce a method for inferring an explicit PDE from a data sample generated by previously unseen dynamics, based on a learned context. The training phase integrates knowledge…
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…
Policy Gradients with Variance Related Risk Criteria
Dotan Di Castro, Aviv Tamar, Shie Mannor
Managing risk in dynamic decision problems is of cardinal importance in many fields such as finance and process control. The most common approach to defining risk is through variou…
A Maximal Large Deviation Inequality for Sub-Gaussian Variables
Dotan Di Castro, Claudio Gentile, Shie Mannor
In this short note we prove a maximal concentration lemma for sub-Gaussian random variables stating that for independent sub-Gaussian random variables we have \[P<(\max_{1\le i\le…