Pavithra Harsha

24 papers A* 2B 1Journal 19Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Aligning Learning and Endogenous Decision-Making.
CoRR
Rares Cristian, Pavithra Harsha, Georgia Perakis, Brian Quanz
2025 B conf
Causal Latency Modelling for Cloud Microservices.
CLOUD
Christopher Lohse, Diego Tsutsumi, Amadou Ba, Pavithra Harsha, Chitra Subramanian, Martin Straesser, Marco Ruffini
2025 J jnl
Deep Policy Iteration with Integer Programming for Inventory Management.
Manuf. Serv. Oper. Manag.
Pavithra Harsha, Ashish Jagmohan, Jayant Kalagnanam, Brian Quanz, Divya Singhvi
2025 J jnl
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach.
CoRR
Rares Cristian, Pavithra Harsha, Georgia Perakis, Brian Quanz
2025 — conf
Practical Contextual Bandits for Large-Scale Structured Discrete Constrained Optimization Problems.
KDD (2)
Pavithra Harsha, Chitra Subramanian, Naoki Abe, Shivaram Subramanian, Amadou Ba, Kevin Arturo Fernández Román, Mauricio Longinos Garrido, Chandrasekhar Narayanaswami
2024 J jnl
Inter-Series Transformer: Attending to Products in Time Series Forecasting.
CoRR
Rares Cristian, Pavithra Harsha, Clemente Ocejo, Georgia Perakis, Brian Quanz, Ioannis Spantidakis, Hamza Zerhouni
2024 J jnl
Leveraging Interpretability in the Transformer to Automate the Proactive Scaling of Cloud Resources.
CoRR
Amadou Ba, Pavithra Harsha, Chitra Subramanian
2024 J jnl
Optimal Workload Placement on Multi-Instance GPUs.
CoRR
Bekir O. Turkkan, Pavankumar Murali, Pavithra Harsha, Rohan R. Arora, Gerard Vanloo, Chandra Narayanaswami
2023 J jnl
An Optimistic-Robust Approach for Dynamic Positioning of Omnichannel Inventories.
CoRR
Pavithra Harsha, Shivaram Subramanian, Ali Koc, Mahesh Ramakrishna, Brian Quanz, Dhruv Shah, Chandra Narayanaswami
2023 A* conf
End-to-End Learning for Optimization via Constraint-Enforcing Approximators.
AAAI
Rares Cristian, Pavithra Harsha, Georgia Perakis, Brian Leo Quanz, Ioannis Spantidakis
2023 A* conf
Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting.
KDD
Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami
2022 J jnl
Hierarchy-guided Model Selection for Time Series Forecasting.
CoRR
Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami
2022 J jnl
Learning Personalized Product Recommendations with Customer Disengagement.
Manuf. Serv. Oper. Manag.
Hamsa Bastani, Pavithra Harsha, Georgia Perakis, Divya Singhvi
2021 J jnl
A Prescriptive Machine-Learning Framework to the Price-Setting Newsvendor Problem.
INFORMS J. Optim.
Pavithra Harsha, Ramesh Natarajan, Dharmashankar Subramanian
2021 J jnl
Demand Modeling in the Presence of Unobserved Lost Sales.
Manag. Sci.
Shivaram Subramanian, Pavithra Harsha
2021 J jnl
Math Programming based Reinforcement Learning for Multi-Echelon Inventory Management.
CoRR
Pavithra Harsha, Ashish Jagmohan, Jayant R. Kalagnanam, Brian Quanz, Divya Singhvi
2020 J jnl
A Data-Driven Approach to Personalized Bundle Pricing and Recommendation.
Manuf. Serv. Oper. Manag.
Markus Ettl, Pavithra Harsha, Anna Papush, Georgia Perakis
2020 J jnl
Designing Price Incentives in a Network with Social Interactions.
Manuf. Serv. Oper. Manag.
Maxime C. Cohen, Pavithra Harsha
2019 J jnl
A Practical Price Optimization Approach for Omnichannel Retailing.
INFORMS J. Optim.
Pavithra Harsha, Shivaram Subramanian, Markus Ettl
2019 J jnl
Dynamic Pricing of Omnichannel Inventories.
Manuf. Serv. Oper. Manag.
Pavithra Harsha, Shivaram Subramanian, Joline Uichanco
2019 J jnl
Special Issue of
INFORMS J. Appl. Anal.
Burcu B. Keskin, Pavithra Harsha
2013 J jnl
A Framework for the Analysis of Probabilistic Demand Response Schemes.
IEEE Trans. Smart Grid
Pavithra Harsha, Mayank Sharma, Ramesh Natarajan, Soumyadip Ghosh
2011 — conf
Optimal sizing of energy storage for efficient integration of renewable energy.
CDC/ECC
Pavithra Harsha, Munther A. Dahleh
2010 J jnl
Strong activity rules for iterative combinatorial auctions.
Comput. Oper. Res.
Pavithra Harsha, Cynthia Barnhart, David C. Parkes, Haoqi Zhang