254 citations · 882 across the 66 of their papers we have counts for
9 papers · 1 filter
Central Limit Theorems for Smooth Optimal Transport Maps
Tudor Manole, Sivaraman Balakrishnan, Jonathan Niles-Weed +1
One of the central objects in the theory of optimal transport is the Brenier map: the unique monotone transformation which pushes forward an absolutely continuous probability law o…
Conservative Inference for Counterfactuals
Sivaraman Balakrishnan, Edward Kennedy, Larry Wasserman
In causal inference, the joint law of a set of counterfactual random variables is generally not identified. We show that a conservative version of the joint law - corresponding to…
Causal Effect Estimation after Propensity Score Trimming with Continuous Treatments
Zach Branson, Edward H. Kennedy, Sivaraman Balakrishnan +1
Propensity score trimming, which discards subjects with propensity scores below a threshold, is a common way to address positivity violations that complicate causal effect estimati…
Nearly Minimax Optimal Wasserstein Conditional Independence Testing
Matey Neykov, Larry Wasserman, Ilmun Kim +1
This paper is concerned with minimax conditional independence testing. In contrast to some previous works on the topic, which use the total variation distance to separate the null…
Conditional Independence Testing for Discrete Distributions: Beyond - and -tests
Ilmun Kim, Matey Neykov, Sivaraman Balakrishnan +1
This paper is concerned with the problem of conditional independence testing for discrete data. In recent years, researchers have shed new light on this fundamental problem, emphas…
Robust Universal Inference For Misspecified Models
Beomjo Park, Sivaraman Balakrishnan, Larry Wasserman
In statistical inference, it is rarely realistic that the hypothesized statistical model is well-specified, and consequently it is important to understand the effects of misspecifi…
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms
Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen +3
This paper focuses on supervised and unsupervised online label shift, where the class marginals varies but the class-conditionals remain invariant. In the unsupervi…
The Fundamental Limits of Structure-Agnostic Functional Estimation
Sivaraman Balakrishnan, Edward H. Kennedy, Larry Wasserman
Many recent developments in causal inference, and functional estimation problems more generally, have been motivated by the fact that classical one-step (first-order) debiasing met…
RLSbench: Domain Adaptation Under Relaxed Label Shift
Saurabh Garg, Nick Erickson, James Sharpnack +3
Despite the emergence of principled methods for domain adaptation under label shift, their sensitivity to shifts in class conditional distributions is precariously under explored.…