A Graph Partitioning Approach to Simultaneous Angular Reconstitution. - Gabi Pragier; Ido Greenberg; Xiuyuan Cheng; Yoel Shkolnisky (IEEE Trans. Computational Imaging, 2016)

Drift Detection in Episodic Data: Detect When Your Agent Starts Faltering. - Ido Greenberg; Shie Mannor (CoRR, 2020)

Detecting Rewards Deterioration in Episodic Reinforcement Learning. - Ido Greenberg; Shie Mannor (ICML, 2021)

Using Kalman Filter The Right Way: Noise Estimation Is Not Optimal. - Ido Greenberg; Shie Mannor; Netanel Yannay (CoRR, 2021)

Efficient Risk-Averse Reinforcement Learning. - Ido Greenberg; Yinlam Chow; Mohammad Ghavamzadeh; Shie Mannor (NeurIPS, 2022)

Continuous Forecasting via Neural Eigen Decomposition of Stochastic Dynamics. - Stav Belogolovsky; Ido Greenberg; Danny Eytan; Shie Mannor (CoRR, 2022)

Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning. - Deborah Cohen; Moonkyung Ryu; Yinlam Chow; Orgad Keller; Ido Greenberg; Avinatan Hassidim; Michael Fink; Yossi Matias; Idan Szpektor; Craig Boutilier; Gal Elidan (CoRR, 2022)

Individualized Dosing Dynamics via Neural Eigen Decomposition. - Stav Belogolovsky; Ido Greenberg; Danny Eytan; Shie Mannor (NeurIPS, 2023)

Train Hard, Fight Easy: Robust Meta Reinforcement Learning. - Ido Greenberg; Shie Mannor; Gal Chechik; Eli A. Meirom (NeurIPS, 2023)

Optimization or Architecture: How to Hack Kalman Filtering. - Ido Greenberg; Netanel Yannay; Shie Mannor (NeurIPS, 2023)

Accelerating Vehicle Routing via AI-Initialized Genetic Algorithms. - Ido Greenberg; Piotr Sielski; Hugo Linsenmaier; Rajesh Gandham; Shie Mannor; Alexandre Fender; Gal Chechik; Eli A. Meirom (CoRR, 2025)