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Aditya Gangrade
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2020 – today
- 2024
- [c14]Aditya Gangrade, Tianrui Chen, Venkatesh Saligrama:
Safe Linear Bandits over Unknown Polytopes. COLT 2024: 1755-1795 - [c13]Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama, Clayton Scott:
Testing the Feasibility of Linear Programs with Bandit Feedback. ICML 2024 - [i11]Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama, Clayton Scott:
Testing the Feasibility of Linear Programs with Bandit Feedback. CoRR abs/2406.15648 (2024) - 2023
- [c12]Anil Kag, Durmus Alp Emre Acar, Aditya Gangrade, Venkatesh Saligrama:
Scaffolding a Student to Instill Knowledge. ICLR 2023 - [c11]Anil Kag, Igor Fedorov, Aditya Gangrade, Paul N. Whatmough, Venkatesh Saligrama:
Efficient Edge Inference by Selective Query. ICLR 2023 - [c10]Yo Joong Choe, Aditya Gangrade, Aaditya Ramdas:
Counterfactually Comparing Abstaining Classifiers. NeurIPS 2023 - [i10]Yo Joong Choe, Aditya Gangrade, Aaditya Ramdas:
Counterfactually Comparing Abstaining Classifiers. CoRR abs/2305.10564 (2023) - 2022
- [c9]Tianrui Chen, Aditya Gangrade, Venkatesh Saligrama:
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. ICML 2022: 3123-3148 - [i9]Tianrui Chen, Aditya Gangrade, Venkatesh Saligrama:
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. CoRR abs/2204.00706 (2022) - [i8]Tianrui Chen, Aditya Gangrade, Venkatesh Saligrama:
A Doubly Optimistic Strategy for Safe Linear Bandits. CoRR abs/2209.13694 (2022) - 2021
- [c8]Aditya Gangrade, Anil Kag, Venkatesh Saligrama:
Selective Classification via One-Sided Prediction. AISTATS 2021: 2179-2187 - [c7]Aditya Gangrade, Anil Kag, Ashok Cutkosky, Venkatesh Saligrama:
Online Selective Classification with Limited Feedback. NeurIPS 2021: 14529-14541 - [i7]Aditya Gangrade, Anil Kag, Ashok Cutkosky, Venkatesh Saligrama:
Online Selective Classification with Limited Feedback. CoRR abs/2110.14243 (2021) - 2020
- [c6]Durmus Alp Emre Acar, Aditya Gangrade, Venkatesh Saligrama:
Budget Learning via Bracketing. AISTATS 2020: 4109-4119 - [c5]Ali Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama:
Piecewise Linear Regression via a Difference of Convex Functions. ICML 2020: 8895-8904 - [c4]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Limits on Testing Structural Changes in Ising Models. NeurIPS 2020 - [i6]Aditya Gangrade, Durmus Alp Emre Acar, Venkatesh Saligrama:
Budget Learning via Bracketing. CoRR abs/2004.06298 (2020) - [i5]Ali Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama:
Piecewise Linear Regression via a Difference of Convex Functions. CoRR abs/2007.02422 (2020) - [i4]Aditya Gangrade, Anil Kag, Venkatesh Saligrama:
Selective Classification via One-Sided Prediction. CoRR abs/2010.07853 (2020) - [i3]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Limits on Testing Structural Changes in Ising Models. CoRR abs/2011.03678 (2020)
2010 – 2019
- 2019
- [c3]Aditya Gangrade, Praveen Venkatesh, Bobak Nazer, Venkatesh Saligrama:
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models. NeurIPS 2019: 10364-10375 - 2018
- [c2]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds. ICASSP 2018: 6931-6935 - [i2]Aditya Gangrade, Praveen Venkatesh, Bobak Nazer, Venkatesh Saligrama:
Testing Changes in Communities for the Stochastic Block Model. CoRR abs/1812.00769 (2018) - 2017
- [c1]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Lower bounds for two-sample structural change detection in ising and Gaussian models. Allerton 2017: 1016-1025 - [i1]Aditya Gangrade, Bobak Nazer, Venkatesh Saligrama:
Lower Bounds for Two-Sample Structural Change Detection in Ising and Gaussian Models. CoRR abs/1710.10366 (2017)
Coauthor Index
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