Raj Agrawal

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 14

Top Topics

High Dimensions

Causal Structure

Police Department

Pairwise Interactions

Top Venues

J. Mach. Learn. Res.

Publications

Raj Agrawal, Sam Witty, Andy Zane, Eli Bingham
Automated Efficient Estimation using Monte Carlo Efficient Influence Functions. CoRR (2024)
Raj Agrawal, Tamara Broderick
The SKIM-FA Kernel: High-Dimensional Variable Selection and Nonlinear Interaction Discovery in Linear Time. J. Mach. Learn. Res. 24 (2023)
Chandler Squires, Annie Yun, Eshaan Nichani, Raj Agrawal, Caroline Uhler
Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors. CLeaR (2022)
Thibaut Horel, Lorenzo Masoero, Raj Agrawal, Daria Roithmayr, Trevor Campbell
The CPD Data Set: Personnel, Use of Force, and Complaints in the Chicago Police Department. NeurIPS Datasets and Benchmarks (2021)
Charles C. Margossian, Aki Vehtari, Daniel Simpson, Raj Agrawal
Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond. NeurIPS (2020)
Brian L. Trippe, Jonathan H. Huggins, Raj Agrawal, Tamara Broderick
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations. ICML (2019)
Brian L. Trippe, Jonathan H. Huggins, Raj Agrawal, Tamara Broderick
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations. CoRR (2019)
Raj Agrawal, Trevor Campbell, Jonathan H. Huggins, Tamara Broderick
Data-dependent compression of random features for large-scale kernel approximation. AISTATS (2019)
Raj Agrawal, Brian L. Trippe, Jonathan H. Huggins, Tamara Broderick
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions. ICML (2019)
Raj Agrawal, Chandler Squires, Karren D. Yang, Karthikeyan Shanmugam, Caroline Uhler
ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery. AISTATS (2019)
Raj Agrawal, Jonathan H. Huggins, Brian L. Trippe, Tamara Broderick
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions. CoRR (2019)
Raj Agrawal, Tamara Broderick, Caroline Uhler
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models. CoRR (2018)
Raj Agrawal, Trevor Campbell, Jonathan H. Huggins, Tamara Broderick
Data-dependent compression of random features for large-scale kernel approximation. CoRR (2018)
Raj Agrawal, Caroline Uhler, Tamara Broderick
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models. ICML (2018)