Robust End-to-End Learning under Endogenous Uncertainty.
Submitted to ICLR (International Conference on Learning Representations) 2025.
With Georgia Perakis and IBM collaborators (Pavithra Harsha, Brian Quanz)
A Discretization Framework for Robust Contextual Stochastic Optimization.
Accepted in ICLR (International Conference on Learning Representations) 2024.
Expanded version received Revise and Resubmit at Management Science Journal with revision submitted.
With Georgia Perakis
End-to-End Learning for Optimization via Constraint-Enforcing Approximators.
Accepted in AAAI (Association for the Advancement of Artificial Intelligence) 2023.
Accepted in AI for Decision Optimization Workshop of the AAAI Conference 2022.
Expanded version received Revise and Resubmit at Management Science Journal with revision submitted.
With Georgia Perakis and IBM collaborators (Pavithra Harsha, Brian Quanz)
The role of optimization in some recent advances in data-driven decision-making.
Accepted in Mathematical Programming 2022.
With Lennart Baardman, Georgia Perakis, Divya Singhvi, Omar Skali Lami, Leann Thayaparan.
Tractable inventory allocation using fulfillment rules and end-to-end learning.
Submitted to POM (Production and Operations Management Journal).
With Georgia Perakis and collabators from IBM (Pavithra Harsha, Brian Quanz) and Amazon (Ioannis Spantidakis).
Inter-Series Transformer: Attending to Products in Time Series Forecasting
Submitted to IJF (International Journal of Forecasting). Received Revise and Resubmit and revision submitted.
With Pavithra Harsha, Clemente Ocejo, Georgia Perakis, Brian Quanz, Ioannis Spantidakis, Hamza Zerhouni.
Coherency Loss for Hierarchical Time Series Forecasting
Accepted with oral presentation at KDD 2024 workshop (10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs).
Submitted to AAAI 2025.
With Georgia Perakis and IBM collaborators (Pavithra Harsha, Brian Quanz, Michael Hensgen)
Talks
Robust End-to-End Learning under Endogenous Uncertainty
- 2024 INFORMS
- 2024 M&SOM Conference
- 2024 Interational Symposia on Mathematical Programming (ISMP)
- 2024 IBM internal guest talk
A Discretization Framework for Robust Contextual Stochastic Optimization
- 2024 Princeton Workshop on Optimization, Learning, and Control
- 2024 ICLR Conference
- 2023 INFORMS Annual Meeting
End-to-End Learning for Optimization via Constraint-Enforcing Approximators
- 2023 AAAI Conference
- 2022 INFORMS Annual Meeting
- 2022 Production and Operations Management Society Conference
- 2022 MIT-IBM Watson AI Lab Poster Session
Coherency Loss for Hierarchical Time Series Forecasting
- 2024 KDD