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ORCIDPavithra Harsha
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2020 – today
- 2024
[i6]Rares Cristian, Pavithra Harsha, Clemente Ocejo, Georgia Perakis, Brian Quanz, Ioannis Spantidakis, Hamza Zerhouni:
Inter-Series Transformer: Attending to Products in Time Series Forecasting. CoRR abs/2408.03872 (2024)- [i5]Amadou Ba, Pavithra Harsha, Chitra Subramanian:
Leveraging Interpretability in the Transformer to Automate the Proactive Scaling of Cloud Resources. CoRR abs/2409.03103 (2024) - [i4]Bekir O. Turkkan, Pavankumar Murali, Pavithra Harsha, Rohan Arora, Gerard Vanloo, Chandra Narayanaswami:
Optimal Workload Placement on Multi-Instance GPUs. CoRR abs/2409.06646 (2024) - 2023
- [c3]Rares Cristian, Pavithra Harsha, Georgia Perakis, Brian Leo Quanz, Ioannis Spantidakis:
End-to-End Learning for Optimization via Constraint-Enforcing Approximators. AAAI 2023: 7253-7260 - [c2]Arindam Jati
, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami:
Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting. KDD 2023: 891-900 - [i3]Pavithra Harsha, Shivaram Subramanian, Ali Koc, Mahesh Ramakrishna, Brian Quanz, Dhruv Shah, Chandra Narayanaswami:
An Optimistic-Robust Approach for Dynamic Positioning of Omnichannel Inventories. CoRR abs/2310.12183 (2023) - 2022
- [j10]Hamsa Bastani, Pavithra Harsha, Georgia Perakis, Divya Singhvi:
Learning Personalized Product Recommendations with Customer Disengagement. Manuf. Serv. Oper. Manag. 24(4): 2010-2028 (2022) - [i2]Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami:
Hierarchy-guided Model Selection for Time Series Forecasting. CoRR abs/2211.15092 (2022) - 2021
- [j9]Pavithra Harsha, Ramesh Natarajan, Dharmashankar Subramanian:
A Prescriptive Machine-Learning Framework to the Price-Setting Newsvendor Problem. INFORMS J. Optim. 3(3): 227-253 (2021) - [j8]Shivaram Subramanian, Pavithra Harsha:
Demand Modeling in the Presence of Unobserved Lost Sales. Manag. Sci. 67(6): 3803-3833 (2021) - [i1]Pavithra Harsha, Ashish Jagmohan, Jayant R. Kalagnanam, Brian Quanz, Divya Singhvi:
Math Programming based Reinforcement Learning for Multi-Echelon Inventory Management. CoRR abs/2112.02215 (2021) - 2020
- [j7]Maxime C. Cohen, Pavithra Harsha:
Designing Price Incentives in a Network with Social Interactions. Manuf. Serv. Oper. Manag. 22(2): 292-309 (2020) - [j6]Markus Ettl, Pavithra Harsha, Anna Papush, Georgia Perakis:
A Data-Driven Approach to Personalized Bundle Pricing and Recommendation. Manuf. Serv. Oper. Manag. 22(3): 461-480 (2020)
2010 – 2019
- 2019
- [j5]Pavithra Harsha, Shivaram Subramanian, Markus Ettl:
A Practical Price Optimization Approach for Omnichannel Retailing. INFORMS J. Optim. 1(3): 241-264 (2019) - [j4]Burcu B. Keskin, Pavithra Harsha:
Special Issue of INFORMS Journal on Applied Analytics - Analytics Behind Designing and Managing Omni-channel Supply Chains. INFORMS J. Appl. Anal. 49(3): 233-234 (2019) - [j3]Pavithra Harsha, Shivaram Subramanian, Joline Uichanco:
Dynamic Pricing of Omnichannel Inventories. Manuf. Serv. Oper. Manag. 21(1): 47-65 (2019) - 2013
- [j2]Pavithra Harsha, Mayank Sharma, Ramesh Natarajan, Soumyadip Ghosh:
A Framework for the Analysis of Probabilistic Demand Response Schemes. IEEE Trans. Smart Grid 4(4): 2274-2284 (2013) - 2011
- [c1]Pavithra Harsha, Munther A. Dahleh:
Optimal sizing of energy storage for efficient integration of renewable energy. CDC/ECC 2011: 5813-5819 - 2010
- [j1]Pavithra Harsha, Cynthia Barnhart, David C. Parkes, Haoqi Zhang:
Strong activity rules for iterative combinatorial auctions. Comput. Oper. Res. 37(7): 1271-1284 (2010)
Coauthor Index
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