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Shiv Shankar
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2020 – today
- 2024
- [c19]Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau:
A/B testing under Interference with Partial Network Information. AISTATS 2024: 19-27 - [c18]Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill:
Adaptive Instrument Design for Indirect Experiments. ICLR 2024 - [c17]Shiv Shankar, Ritwik Sinha, Madalina Fiterau:
On Online Experimentation without Device Identifiers. ICML 2024 - [i19]Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau:
A/B testing under Interference with Partial Network Information. CoRR abs/2404.10547 (2024) - 2023
- [c16]Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Madalina Fiterau:
Direct Inference of Effect of Treatment (DIET) for a Cookieless World. AISTATS 2023: 1869-1887 - [c15]Shiv Shankar:
Implicit Training of Inference Network Models for Structured Prediction. UAI 2023: 1889-1899 - [c14]Shiv Shankar
, Ritwik Sinha
Privacy Aware Experiments without Cookies. WSDM 2023: 1144-1147 - [i18]Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno Castro da Silva, Emma Brunskill, Philip S. Thomas:
Off-Policy Evaluation for Action-Dependent Non-Stationary Environments. CoRR abs/2301.10330 (2023) - [i17]Yash Chandak, Shiv Shankar, Venkata Gandikota
Optimization using Parallel Gradient Evaluations on Multiple Parameters. CoRR abs/2302.03161 (2023) - [i16]Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill:
Adaptive Instrument Design for Indirect Experiments. CoRR abs/2312.02438 (2023) - 2022
- [c13]Shiv Shankar:
Multimodal fusion via cortical network inspired losses. ACL (1) 2022: 1167-1178 - [c12]Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno C. da Silva, Emma Brunskill, Philip S. Thomas:
Off-Policy Evaluation for Action-Dependent Non-stationary Environments. NeurIPS 2022 - [i15]Shiv Shankar, Laure Thompson, Madalina Fiterau:
Progressive Fusion for Multimodal Integration. CoRR abs/2209.00302 (2022) - [i14]Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Viswanathan Swaminathan, Sridhar Mahadevan:
Privacy Aware Experiments without Cookies. CoRR abs/2211.03758 (2022) - [i13]Shiv Shankar, Vihari Piratla:
Implicit Training of Energy Model for Structure Prediction. CoRR abs/2211.11649 (2022) - 2021
- [c11]Yash Chandak, Shiv Shankar, Philip S. Thomas:
High-Confidence Off-Policy (or Counterfactual) Variance Estimation. AAAI 2021: 6939-6947 - [c10]Shiv Shankar, Don Towsley
Bosonic Random Walk Neural Networks for Graph Learning. COMPLEX NETWORKS 2021: 401-411 - [c9]Shiv Shankar, Daniel Sheldon:
Sibling Regression for Generalized Linear Models. ECML/PKDD (2) 2021: 781-795 - [i12]Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich:
Three-quarter Sibling Regression for Denoising Observational Data. CoRR abs/2101.00074 (2021) - [i11]Shiv Shankar, Don Towsley:
Bosonic Random Walk Networks for Graph Learning. CoRR abs/2101.00082 (2021) - [i10]Yash Chandak, Shiv Shankar, Philip S. Thomas:
High-Confidence Off-Policy (or Counterfactual) Variance Estimation. CoRR abs/2101.09847 (2021) - [i9]Shiv Shankar, Daniel Sheldon:
Sibling Regression for Generalized Linear Models. CoRR abs/2107.01338 (2021) - [i8]Shiv Shankar:
Adversarial Stein Training for Graph Energy Models. CoRR abs/2108.12982 (2021) - [i7]Shiv Shankar:
Neural Dependency Coding inspired Multimodal Fusion. CoRR abs/2110.00385 (2021) - 2020
- [c8]MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis:
Differential Equation Units: Learning Functional Forms of Activation Functions from Data. AAAI 2020: 6030-6037 - [c7]Frank Bentley, Josh Jacobson, Charlotte Sperling, Shiv Shankar, Chris Royer, Ian McCarthy:
Rethinking Consumer Email: The Research Process for Yahoo Mail 6. CHI Extended Abstracts 2020: 1-6 - [c6]Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas:
Optimizing for the Future in Non-Stationary MDPs. ICML 2020: 1414-1425 - [i6]Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas:
Optimizing for the Future in Non-Stationary MDPs. CoRR abs/2005.08158 (2020) - [i5]Vihari Piratla, Shiv Shankar:
Untapped Potential of Data Augmentation: A Domain Generalization Viewpoint. CoRR abs/2007.04662 (2020)
2010 – 2019
- 2019
- [c5]Shiv Shankar, Sunita Sarawagi:
Posterior Attention Models for Sequence to Sequence Learning. ICLR (Poster) 2019 - [c4]Shiv Shankar, Daniel Sheldon, Tao Sun
Three-quarter Sibling Regression for Denoising Observational Data. IJCAI 2019: 5960-5966 - [i4]MohamadAli Torkamani, Phillip Wallis, Shiv Shankar, Amirmohammad Rooshenas:
Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions. CoRR abs/1905.07685 (2019) - [i3]MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis:
Differential Equation Units: Learning Functional Forms of Activation Functions from Data. CoRR abs/1909.03069 (2019) - 2018
- [c3]Shiv Shankar, Sunita Sarawagi:
Labeled Memory Networks for Online Model Adaptation. AAAI 2018: 4034-4041 - [c2]Shiv Shankar, Siddhant Garg, Sunita Sarawagi:
Surprisingly Easy Hard-Attention for Sequence to Sequence Learning. EMNLP 2018: 640-645 - [c1]Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, Sunita Sarawagi:
Generalizing Across Domains via Cross-Gradient Training. ICLR (Poster) 2018 - [i2]Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, Sunita Sarawagi:
Generalizing Across Domains via Cross-Gradient Training. CoRR abs/1804.10745 (2018) - 2017
- [i1]Shiv Shankar, Sunita Sarawagi:
Label Organized Memory Augmented Neural Network. CoRR abs/1707.01461 (2017)
Coauthor Index
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last updated on 2024-09-04 01:25 CEST by the dblp team
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