Orit Davidovich

Publications

• Mitigating the curse of detail: Scaling arguments for feature learning and sample complexity

  • • Noa Rubin
    • Orit Davidovich
    • et al.
  • 2026
  • ICLR 2026

  Conference paper

• Heuristics for Combinatorial Optimization via Value-based Reinforcement Learning: A Unified Framework and Analysis

  • • Orit Davidovich
    • Shimrit Shtern
    • et al.
  • 2025
  • arXiv

  Paper

• Going Topological in Multi-risk Extended Markov Ratio Decision Processes

  • • Alexander Zadorojniy
    • Orit Davidovich
    • et al.
  • 2025
  • ICAPS 2025

  Conference paper

• Finding Probably Approximate Optimal Solutions by Training to Estimate the Optimal Values of Subproblems

  • • Nimrod Megiddo
    • Segev Wasserkrug
    • et al.
  • 2025
  • arXiv

  Paper

• A Rigorous Risk-aware Linear Approach to Extended Markov Ratio Decision Processes with Embedded Learning

  • • Alexander Zadorojniy
    • Takayuki Osogami
    • et al.
  • 2023
  • IJCAI 2023

  Conference paper

• Optimization with Constraint Learning

  • • S. Ilker Birbil
    • Donato Maragno
    • et al.
  • 2023
  • AAAI 2023

  Tutorial

• The Good, the Bad, and the Outliers: A Testing Framework for Decision Optimization Model Learning

  • • Orit Davidovich
    • Gheorghe-Teodor Bercea
    • et al.
  • 2022
  • KDD 2022

  Conference paper

• Addressing Solution Quality in Data-generated Optimization Models

  • • Orit Davidovich
    • Parikshit Ram
    • et al.
  • 2022
  • AAAI 2022

  Workshop paper

• Data and Knowledge Driven Optimization Model Generation for Flow Based Optimization Problems

  • • Dharmashankar Subramanian
    • Segev Wasserkrug
    • et al.
  • 2021
  • INFORMS 2021

  Talk

• The Combinatorial Generation of Objective Targets and Constraints for Large-scale Testing of Optimization Routines

  • • Orit Davidovich
  • 2021
  • FWCG 2021

  Workshop paper