Raghavendra Addanki

According to our database, Raghavendra Addanki authored at least 16 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Causal Discovery-Driven Change Point Detection in Time Series.

Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu

CoRR, 2024

Continuous Treatment Effects with Surrogate Outcomes.

Zhenghao Zeng, David Arbour, Avi Feller, Raghavendra Addanki, Ryan A. Rossi, Ritwik Sinha, Edward H. Kennedy

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Limits of Approximating the Median Treatment Effect.

Raghavendra Addanki, Siddharth Bhandari

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Anytime-Valid Confidence Sequences in an Enterprise A/B Testing Platform.

Akash Maharaj, Ritwik Sinha, David Arbour, Ian Waudby-Smith, Simon Z. Liu, Moumita Sinha, Raghavendra Addanki, Aaditya Ramdas, Manas Garg, Viswanathan Swaminathan

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Causal Discovery in Semi-Stationary Time Series.

Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Sample Constrained Treatment Effect Estimation.

Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improved Approximation and Scalability for Fair Max-Min Diversification.

Raghavendra Addanki, Andrew McGregor, Alexandra Meliou, Zafeiria Moumoulidou

Proceedings of the 25th International Conference on Database Theory, 2022

Non-Adaptive Edge Counting and Sampling via Bipartite Independent Set Queries.

Raghavendra Addanki, Andrew McGregor, Cameron Musco

Proceedings of the 30th Annual European Symposium on Algorithms, 2022

2021

How to Design Robust Algorithms using Noisy Comparison Oracle.

Raghavendra Addanki, Sainyam Galhotra, Barna Saha

Proc. VLDB Endow., 2021

Collaborative Causal Discovery with Atomic Interventions.

Raghavendra Addanki, Shiva Prasad Kasiviswanathan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Intervention Efficient Algorithms for Approximate Learning of Causal Graphs.

Raghavendra Addanki, Andrew McGregor, Cameron Musco

Proceedings of the Algorithmic Learning Theory, 2021

2020

Search Result Diversification with Guarantee of Topic Proportionality.

Sheikh Muhammad Sarwar, Raghavendra Addanki, Ali Montazeralghaem, Soumyabrata Pal, James Allan

Proceedings of the ICTIR '20: The 2020 ACM SIGIR International Conference on the Theory of Information Retrieval, 2020

Efficient Intervention Design for Causal Discovery with Latents.

Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare Analytics.

Khushbu Agarwal, Tome Eftimov, Raghavendra Addanki, Sutanay Choudhury, Suzanne Tamang, Robert Rallo

CoRR, 2019

Dynamic set cover: improved algorithms and lower bounds.

Amir Abboud, Raghavendra Addanki, Fabrizio Grandoni, Debmalya Panigrahi, Barna Saha

Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

2018

Fully Dynamic Set Cover - Improved and Simple.

Raghavendra Addanki, Barna Saha

CoRR, 2018