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06/02/2023
Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization
We introduce efficient (1+ε)-approximation algorithms for the binary mat...
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03/10/2023
Exphormer: Sparse Transformers for Graphs
Graph transformers have emerged as a promising architecture for a variet...
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06/23/2022
Affinity-Aware Graph Networks
Graph Neural Networks (GNNs) have emerged as a powerful technique for le...
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12/07/2021
Private Robust Estimation by Stabilizing Convex Relaxations
We give the first polynomial time and sample (ϵ, δ)-differentially priva...
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06/24/2021
Linear Space Streaming Lower Bounds for Approximating CSPs
We consider the approximability of constraint satisfaction problems in t...
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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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02/05/2020
Pure Differentially Private Summation from Anonymous Messages
The shuffled (aka anonymous) model has recently generated significant in...
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09/24/2019
Private Aggregation from Fewer Anonymous Messages
Consider the setup where n parties are each given a number x_i ∈F_q and ...
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09/03/2019
Oblivious Sketching of High-Degree Polynomial Kernels
Kernel methods are fundamental tools in machine learning that allow dete...
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08/29/2019
Private Heavy Hitters and Range Queries in the Shuffled Model
An exciting new development in differential privacy is the shuffled mode...
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06/19/2019
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model
Federated learning promises to make machine learning feasible on distrib...
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02/27/2019
Dimension-independent Sparse Fourier Transform
The Discrete Fourier Transform (DFT) is a fundamental computational prim...
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12/20/2018
A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms
Reconstructing continuous signals from a small number of discrete sample...
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04/26/2018