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02/24/2021
Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm
We study the function space characterization of the inductive bias resul...
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05/03/2020
A Study of Performance of Optimal Transport
We investigate the problem of efficiently computing optimal transport (O...
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04/23/2020
Non-Adaptive Adaptive Sampling on Turnstile Streams
Adaptive sampling is a useful algorithmic tool for data summarization pr...
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03/21/2020
Scaling up Kernel Ridge Regression via Locality Sensitive Hashing
Random binning features, introduced in the seminal paper of Rahimi and R...
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02/19/2020
Randomized Smoothing of All Shapes and Sizes
Randomized smoothing is a recently proposed defense against adversarial ...
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10/09/2019
Scalable Nearest Neighbor Search for Optimal Transport
The Optimal Transport (a.k.a. Wasserstein) distance is an increasingly p...
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06/09/2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
Recent works have shown the effectiveness of randomized smoothing as a s...
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04/03/2019
SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search
We present new secure protocols for approximate k-nearest neighbor searc...
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02/07/2019
On Mean Estimation for General Norms with Statistical Queries
We study the problem of mean estimation for high-dimensional distributio...
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01/24/2019
Learning Sublinear-Time Indexing for Nearest Neighbor Search
Most of the efficient sublinear-time indexing algorithms for the high-di...
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01/24/2019
Learning Space Partitions for Nearest Neighbor Search
Space partitions of R^d underlie a vast and important class of fast near...
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11/15/2018
Adversarial Examples from Cryptographic Pseudo-Random Generators
In our recent work (Bubeck, Price, Razenshteyn, arXiv:1805.10204) we arg...
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11/08/2018
Nonlinear Dimension Reduction via Outer Bi-Lipschitz Extensions
We introduce and study the notion of an outer bi-Lipschitz extension of ...
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11/08/2018
Performance of Johnson-Lindenstrauss Transform for k-Means and k-Medians Clustering
Consider an instance of Euclidean k-means or k-medians clustering. We sh...
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06/26/2018
Approximate Nearest Neighbor Search in High Dimensions
The nearest neighbor problem is defined as follows: Given a set P of n p...
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05/25/2018
Adversarial examples from computational constraints
Why are classifiers in high dimension vulnerable to "adversarial" pertur...
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11/05/2017