
LearningAugmented Sketches for Hessians
Sketching is a dimensionality reduction technique where one compresses a...
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Subspace exploration: Bounds on Projected Frequency Estimation
Given an n × d dimensional dataset A, a projection query specifies a sub...
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Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
We introduce a new scalable approximation for Gaussian processes with pr...
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Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators
We introduce difference estimators for data stream computation, which pr...
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ReducedRank Regression with Operator Norm Error
A common data analysis task is the reducedrank regression problem: ...
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QuantumInspired Algorithms from Randomized Numerical Linear Algebra
We create classical (nonquantum) dynamic data structures supporting que...
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Hutch++: Optimal Stochastic Trace Estimation
We study the problem of estimating the trace of a matrix A that can only...
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Optimal ℓ_1 Column Subset Selection and a Fast PTAS for Low Rank Approximation
We study the problem of entrywise ℓ_1 low rank approximation. We give th...
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On Learned Sketches for Randomized Numerical Linear Algebra
We study "learningbased" sketching approaches for diverse tasks in nume...
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WOR and p's: Sketches for ℓ_pSampling Without Replacement
Weighted sampling is a fundamental tool in data analysis and machine lea...
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Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling
To accelerate kernel methods, we propose a near input sparsity time algo...
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Streaming Complexity of SVMs
We study the space complexity of solving the biasregularized SVM proble...
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VectorMatrixVector Queries for Solving Linear Algebra, Statistics, and Graph Problems
We consider the general problem of learning about a matrix through vecto...
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Approximation Algorithms for Sparse Principal Component Analysis
We present three provably accurate, polynomial time, approximation algor...
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How to reduce dimension with PCA and random projections?
In our "big data" age, the size and complexity of data is steadily incre...
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NonAdaptive Adaptive Sampling on Turnstile Streams
Adaptive sampling is a useful algorithmic tool for data summarization pr...
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Average Case Column Subset Selection for Entrywise ℓ_1Norm Loss
We study the column subset selection problem with respect to the entrywi...
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A Framework for Adversarially Robust Streaming Algorithms
We investigate the adversarial robustness of streaming algorithms. In th...
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LSFJoin: Locality Sensitive Filtering for Distributed AllPairs Set Similarity Under Skew
Allpairs set similarity is a widely used data mining task, even for lar...
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Span Recovery for Deep Neural Networks with Applications to Input Obfuscation
The tremendous success of deep neural networks has motivated the need to...
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Strong Coresets for Subspace Approximation and kMedian in Nearly Linear Time
Recently the first (1+ϵ)approximate strong coresets for kmedian and su...
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Sublinear Time Numerical Linear Algebra for Structured Matrices
We show how to solve a number of problems in numerical linear algebra, s...
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Robust and Sample Optimal Algorithms for PSD LowRank Approximation
Recently, Musco and Woodruff (FOCS, 2017) showed that given an n × n pos...
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Pseudodeterministic Streaming
A pseudodeterministic algorithm is a (randomized) algorithm which, when...
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Graph Spanners in the MessagePassing Model
Graph spanners are sparse subgraphs which approximately preserve all pai...
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Optimal Sketching for Kronecker Product Regression and Low Rank Approximation
We study the Kronecker product regression problem, in which the design m...
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Total Least Squares Regression in Input Sparsity Time
In the total least squares problem, one is given an m × n matrix A, and ...
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The Query Complexity of Mastermind with ℓ_p Distances
Consider a variant of the Mastermind game in which queries are ℓ_p dista...
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Towards Optimal Moment Estimation in Streaming and Distributed Models
One of the oldest problems in the data stream model is to approximate th...
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The Communication Complexity of Optimization
We consider the communication complexity of a number of distributed opti...
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Querying a Matrix through MatrixVector Products
We consider algorithms with access to an unknown matrix M∈F^n × d via ma...
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Separating kPlayer from tPlayer OneWay Communication, with Applications to Data Streams
In a kparty communication problem, the k players with inputs x_1, x_2, ...
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Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel kmeans Clustering
We present tight lower bounds on the number of kernel evaluations requir...
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Dimensionality Reduction for Tukey Regression
We give the first dimensionality reduction methods for the overconstrain...
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LowRank Approximation from Communication Complexity
In lowrank approximation with missing entries, given A∈R^n× n and binar...
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Tight Bounds for the Subspace Sketch Problem with Applications
In the subspace sketch problem one is given an n× d matrix A with O((nd)...
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Weighted Reservoir Sampling from Distributed Streams
We consider messageefficient continuous random sampling from a distribu...
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Optimal Random Sampling from Distributed Streams Revisited
We give an improved algorithm for drawing a random sample from a large d...
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The OneWay Communication Complexity of Dynamic Time Warping Distance
We resolve the randomized oneway communication complexity of Dynamic Ti...
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Weighted Maximum Independent Set of Geometric Objects in Turnstile Streams
We study the Maximum Independent Set problem for geometric objects given...
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Learning Two Layer Rectified Neural Networks in Polynomial Time
Consider the following fundamental learning problem: given input example...
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Towards a ZeroOne Law for Entrywise Low Rank Approximation
There are a number of approximation algorithms for NPhard versions of l...
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Testing Matrix Rank, Optimally
We show that for the problem of testing if a matrix A ∈ F^n × n has rank...
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Sublinear Time LowRank Approximation of Distance Matrices
Let P={ p_1, p_2, ... p_n } and Q = { q_1, q_2 ... q_m } be two point se...
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Strong Coresets for kMedian and Subspace Approximation: Goodbye Dimension
We obtain the first strong coresets for the kmedian and subspace approx...
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Perfect L_p Sampling in a Data Stream
In this paper, we resolve the onepass space complexity of L_p sampling ...
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A PTAS for ℓ_pLow Rank Approximation
A number of recent works have studied algorithms for entrywise ℓ_plow r...
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Leveraging WellConditioned Bases: Streaming & Distributed Summaries in Minkowski pNorms
Work on approximate linear algebra has led to efficient distributed and ...
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Distributed Statistical Estimation of Matrix Products with Applications
We consider statistical estimations of a matrix product over the integer...
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On Sketching the q to p norms
We initiate the study of data dimensionality reduction, or sketching, fo...
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David P. Woodruff
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