
Approximating Sparse PCA from Incomplete Data
We study how well one can recover sparse principal components of a data ...
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Recovering PCA from Hybrid(ℓ_1,ℓ_2) Sparse Sampling of Data Elements
This paper addresses how well we can recover a data matrix when only giv...
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Optimal Sparse Linear AutoEncoders and Sparse PCA
Principal components analysis (PCA) is the optimal linear autoencoder o...
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NPHardness and Inapproximability of Sparse PCA
We give a reduction from clique to establish that sparse PCA is NPhard...
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Comparing Prediction Market Structures, With an Application to Market Making
Ensuring sufficient liquidity is one of the key challenges for designers...
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Random Projections for Linear Support Vector Machines
Let X be a data matrix of rank ρ, whose rows represent n points in ddim...
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The Fast Cauchy Transform and Faster Robust Linear Regression
We provide fast algorithms for overconstrained ℓ_p regression and relate...
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NearOptimal Target Learning With Stochastic Binary Signals
We study learning in a noisy bisection model: specifically, Bayesian alg...
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Network Signatures from Image Representation of Adjacency Matrices: Deep/Transfer Learning for Subgraph Classification
We propose a novel subgraph image representation for classification of n...
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Examining the Use of Neural Networks for Feature Extraction: A Comparative Analysis using Deep Learning, Support Vector Machines, and KNearest Neighbor Classifiers
Neural networks in many varieties are touted as very powerful machine le...
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A Mathematical Model for Optimal Decisions in a Representative Democracy
Direct democracy is a special case of an ensemble of classifiers, where ...
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Quantifying contribution and propagation of error from computational steps, algorithms and hyperparameter choices in image classification pipelines
Data science relies on pipelines that are organized in the form of inter...
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PDMLLite: Private Distributed Machine Learning from Lighweight Cryptography
Privacy is a major issue in learning from distributed data. Recently the...
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Fast Fixed Dimension L2Subspace Embeddings of Arbitrary Accuracy, With Application to L1 and L2 Tasks
We give a fast oblivious L2embedding of A∈R^n x d to B∈R^r x d satisfyi...
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Machine Learning the Phenomenology of COVID19 From Early Infection Dynamics
We present a datadriven machine learning analysis of COVID19 from its ...
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True Nonlinear Dynamics from Incomplete Networks
We study nonlinear dynamics on complex networks. Each vertex i has a sta...
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Malik MagdonIsmail
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