261 citations · 836 across the 30 of their papers we have counts for
5 papers · 1 filter
Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs, Yihe Dong, Piotr Indyk +2
The Optimal Transport (a.k.a. Wasserstein) distance is an increasingly popular similarity measure for rich data domains, such as images or text documents. This raises the necessity…
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
Hadi Salman, Greg Yang, Jerry Li +4
Recent works have shown the effectiveness of randomized smoothing as a scalable technique for building neural network-based classifiers that are provably robust to -norm ad…
SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search
Hao Chen, Ilaria Chillotti, Yihe Dong +3
The -Nearest Neighbor Search (-NNS) is the backbone of several cloud-based services such as recommender systems, face recognition, and database search on text and images. In…
On Mean Estimation for General Norms with Statistical Queries
Jerry Li, Aleksandar Nikolov, Ilya Razenshteyn +1
We study the problem of mean estimation for high-dimensional distributions, assuming access to a statistical query oracle for the distribution. For a normed space $X = (\mathbb{R}^…
Learning Space Partitions for Nearest Neighbor Search
Yihe Dong, Piotr Indyk, Ilya Razenshteyn +1
Space partitions of underlie a vast and important class of fast nearest neighbor search (NNS) algorithms. Inspired by recent theoretical work on NNS for general metr…