254 citations · 882 across the 66 of their papers we have counts for
7 papers · 1 filter
Universal Inference
Larry Wasserman, Aaditya Ramdas, Sivaraman Balakrishnan
We propose a general method for constructing hypothesis tests and confidence sets that have finite sample guarantees without regularity conditions. We refer to such procedures as "…
Statistical Guarantees for Local Spectral Clustering on Random Neighborhood Graphs
Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani
We study the Personalized PageRank (PPR) algorithm, a local spectral method for clustering, which extracts clusters using locally-biased random walks around a given seed node. In c…
Gaussian Mixture Clustering Using Relative Tests of Fit
Purvasha Chakravarti, Sivaraman Balakrishnan, Larry Wasserman
We consider clustering based on significance tests for Gaussian Mixture Models (GMMs). Our starting point is the SigClust method developed by Liu et al. (2008), which introduces a…
Minimax Confidence Intervals for the Sliced Wasserstein Distance
Tudor Manole, Sivaraman Balakrishnan, Larry Wasserman
Motivated by the growing popularity of variants of the Wasserstein distance in statistics and machine learning, we study statistical inference for the Sliced Wasserstein distance--…
Interactive Martingale Tests for the Global Null
Boyan Duan, Aaditya Ramdas, Sivaraman Balakrishnan +1
Global null testing is a classical problem going back about a century to Fisher's and Stouffer's combination tests. In this work, we present simple martingale analogs of these clas…
Path Length Bounds for Gradient Descent and Flow
Chirag Gupta, Sivaraman Balakrishnan, Aaditya Ramdas
We derive bounds on the path length of gradient descent (GD) and gradient flow (GF) curves for various classes of smooth convex and nonconvex functions. Among other results, we…
A Unified Approach to Robust Mean Estimation
Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar
In this paper, we develop connections between two seemingly disparate, but central, models in robust statistics: Huber's epsilon-contamination model and the heavy-tailed noise mode…