Addanki, Raghavendra

10 publications

AISTATS 2025 Causal Discovery-Driven Change Point Detection in Time Series Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu

NeurIPS 2025 Leveraging Semantic Similarity for Experimentation with AI-Generated Treatments Lei Shi, David Arbour, Raghavendra Addanki, Ritwik Sinha, Avi Feller

NeurIPS 2025 Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization Subhojyoti Mukherjee, Viet Dac Lai, Raghavendra Addanki, Ryan A. Rossi, Seunghyun Yoon, Trung Bui, Anup Rao, Jayakumar Subramanian, Branislav Kveton

ICML 2024 Continuous Treatment Effects with Surrogate Outcomes Zhenghao Zeng, David Arbour, Avi Feller, Raghavendra Addanki, Ryan A. Rossi, Ritwik Sinha, Edward Kennedy

COLT 2024 Limits of Approximating the Median Treatment Effect Raghavendra Addanki, Siddharth Bhandari

NeurIPS 2023 Causal Discovery in Semi-Stationary Time Series Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan Rossi, Murat Kocaoglu

NeurIPS 2022 Sample Constrained Treatment Effect Estimation Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao

NeurIPS 2021 Collaborative Causal Discovery with Atomic Interventions Raghavendra Addanki, Shiva P. Kasiviswanathan

ALT 2021 Intervention Efficient Algorithms for Approximate Learning of Causal Graphs Raghavendra Addanki, Andrew McGregor, Cameron Musco

ICML 2020 Efficient Intervention Design for Causal Discovery with Latents Raghavendra Addanki, Shiva Kasiviswanathan, Andrew Mcgregor, Cameron Musco