94 citations · 229 across the 34 of their papers we have counts for
7 papers · 1 filter
Two-Sided Nearest Neighbors: An adaptive and minimax optimal procedure for matrix completion
Tathagata Sadhukhan, Manit Paul, Raaz Dwivedi
Nearest neighbor (NN) algorithms have been extensively used for missing data problems in recommender systems and sequential decision-making systems. Prior theoretical analysis has…
Supervised Kernel Thinning
Albert Gong, Kyuseong Choi, Raaz Dwivedi
The kernel thinning algorithm of Dwivedi & Mackey (2024) provides a better-than-i.i.d. compression of a generic set of points. By generating high-fidelity coresets of size signific…
Learning Counterfactual Distributions via Kernel Nearest Neighbors
Kyuseong Choi, Jacob Feitelberg, Caleb Chin +2
Consider a setting with multiple units (e.g., individuals, cohorts, geographic locations) and outcomes (e.g., treatments, times, items), where the goal is to learn a multivariate d…
Distributional Matrix Completion via Nearest Neighbors in the Wasserstein Space
Jacob Feitelberg, Kyuseong Choi, Anish Agarwal +1
We study the problem of distributional matrix completion: Given a sparsely observed matrix of empirical distributions, we seek to impute the true distributions associated with both…
FairPair: A Robust Evaluation of Biases in Language Models through Paired Perturbations
Jane Dwivedi-Yu, Raaz Dwivedi, Timo Schick
The accurate evaluation of differential treatment in language models to specific groups is critical to ensuring a positive and safe user experience. An ideal evaluation should have…
Debiased Distribution Compression
Lingxiao Li, Raaz Dwivedi, Lester Mackey
Modern compression methods can summarize a target distribution more succinctly than i.i.d. sampling but require access to a low-bias input sequence like a Markov chain…
Doubly Robust Inference in Causal Latent Factor Models
Alberto Abadie, Anish Agarwal, Raaz Dwivedi +1
This article introduces a new estimator of average treatment effects under unobserved confounding in modern data-rich environments featuring large numbers of units and outcomes. Th…