Shiv Shankar

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 37

Top Topics

Structured Prediction

Ordinary Differential Equations

Top Venues

Publications

Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau
A/B testing under Interference with Partial Network Information. CoRR (2024)
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
Adaptive Instrument Design for Indirect Experiments. ICLR (2024)
Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau
A/B testing under Interference with Partial Network Information. AISTATS (2024)
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
Adaptive Instrument Design for Indirect Experiments. CoRR (2023)
Shiv Shankar
Implicit Training of Inference Network Models for Structured Prediction. UAI (2023)
Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Madalina Fiterau
Direct Inference of Effect of Treatment (DIET) for a Cookieless World. AISTATS (2023)
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 (2023)
Shiv Shankar, Ritwik Sinha, Saayan Mitra, Viswanathan (Vishy) Swaminathan, Sridhar Mahadevan, Moumita Sinha
Privacy Aware Experiments without Cookies. WSDM (2023)
Yash Chandak, Shiv Shankar, Venkata Gandikota, Philip S. Thomas, Arya Mazumdar
Optimization using Parallel Gradient Evaluations on Multiple Parameters. CoRR (2023)
Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Viswanathan Swaminathan, Sridhar Mahadevan
Privacy Aware Experiments without Cookies. CoRR (2022)
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)
Shiv Shankar, Laure Thompson, Madalina Fiterau
Progressive Fusion for Multimodal Integration. CoRR (2022)
Shiv Shankar, Vihari Piratla
Implicit Training of Energy Model for Structure Prediction. CoRR (2022)
Shiv Shankar
Multimodal fusion via cortical network inspired losses. ACL (1) (2022)
Shiv Shankar, Daniel Sheldon
Sibling Regression for Generalized Linear Models. CoRR (2021)
Shiv Shankar
Neural Dependency Coding inspired Multimodal Fusion. CoRR (2021)
Shiv Shankar, Daniel Sheldon
Sibling Regression for Generalized Linear Models. ECML/PKDD (2) (2021)
Shiv Shankar
Adversarial Stein Training for Graph Energy Models. CoRR (2021)
Shiv Shankar, Don Towsley
Bosonic Random Walk Networks for Graph Learning. CoRR (2021)
Yash Chandak, Shiv Shankar, Philip S. Thomas
High-Confidence Off-Policy (or Counterfactual) Variance Estimation. AAAI (2021)
Shiv Shankar, Don Towsley
Bosonic Random Walk Neural Networks for Graph Learning. COMPLEX NETWORKS (2021)
Yash Chandak, Shiv Shankar, Philip S. Thomas
High-Confidence Off-Policy (or Counterfactual) Variance Estimation. CoRR (2021)
Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich
Three-quarter Sibling Regression for Denoising Observational Data. CoRR (2021)
Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas
Optimizing for the Future in Non-Stationary MDPs. CoRR (2020)
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)
Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas
Optimizing for the Future in Non-Stationary MDPs. ICML (2020)
MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis
Differential Equation Units: Learning Functional Forms of Activation Functions from Data. AAAI (2020)
Vihari Piratla, Shiv Shankar
Untapped Potential of Data Augmentation: A Domain Generalization Viewpoint. CoRR (2020)
Shiv Shankar, Sunita Sarawagi
Posterior Attention Models for Sequence to Sequence Learning. ICLR (Poster) (2019)
Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich
Three-quarter Sibling Regression for Denoising Observational Data. IJCAI (2019)
MohamadAli Torkamani, Phillip Wallis, Shiv Shankar, Amirmohammad Rooshenas
Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions. CoRR (2019)
MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis
Differential Equation Units: Learning Functional Forms of Activation Functions from Data. CoRR (2019)
Shiv Shankar, Siddhant Garg, Sunita Sarawagi
Surprisingly Easy Hard-Attention for Sequence to Sequence Learning. EMNLP (2018)
Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, Sunita Sarawagi
Generalizing Across Domains via Cross-Gradient Training. ICLR (Poster) (2018)
Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, Sunita Sarawagi
Generalizing Across Domains via Cross-Gradient Training. CoRR (2018)
Shiv Shankar, Sunita Sarawagi
Labeled Memory Networks for Online Model Adaptation. AAAI (2018)
Shiv Shankar, Sunita Sarawagi
Label Organized Memory Augmented Neural Network. CoRR (2017)