
On the Efficient Evaluation of the Azimuthal Fourier Components of the Green's Function for Helmholtz's Equation in Cylindrical Coordinates
In this manuscript, we develop an efficient algorithm to evaluate the az...
read it

Biwhitening Reveals the Rank of a Count Matrix
Estimating the rank of a corrupted data matrix is an important task in d...
read it

Spectral TopDown Recovery of Latent Tree Models
Modeling the distribution of high dimensional data by a latent tree grap...
read it

Local TwoSample Testing over Graphs and PointClouds by RandomWalk Distributions
Twosample testing is a fundamental tool for scientific discovery. Yet, ...
read it

Deep Gated Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) models can extract informative corr...
read it

Let the Data Choose its Features: Differentiable Unsupervised Feature Selection
Scientific observations often consist of a large number of variables (fe...
read it

DoublyStochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise
A fundamental step in many dataanalysis techniques is the construction ...
read it

Spectral neighbor joining for reconstruction of latent tree models
A key assumption in multiple scientific applications is that the distrib...
read it

The Spectral Underpinning of word2vec
word2vec due to Mikolov et al. (2013) is a word embedding method that is...
read it

Heavytailed kernels reveal a finer cluster structure in tSNE visualisations
Tdistributed stochastic neighbour embedding (tSNE) is a widely used da...
read it

Deep supervised feature selection using Stochastic Gates
In this study, we propose a novel nonparametric embedded feature select...
read it

Defending against Adversarial Images using Basis Functions Transformations
We study the effectiveness of various approaches that defend against adv...
read it

Learning Binary Latent Variable Models: A Tensor Eigenpair Approach
Latent variable models with hidden binary units appear in various applic...
read it

SpectralNet: Spectral Clustering using Deep Neural Networks
Spectral clustering is a leading and popular technique in unsupervised d...
read it

Efficient Algorithms for tdistributed Stochastic Neighborhood Embedding
tdistributed Stochastic Neighborhood Embedding (tSNE) is a method for ...
read it

Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science
If we pick n random points uniformly in [0,1]^d and connect each point t...
read it

DataDriven Tree Transforms and Metrics
We consider the analysis of high dimensional data given in the form of a...
read it

Mahalanonbis Distance Informed by Clustering
A fundamental question in data analysis, machine learning and signal pro...
read it

Unsupervised Ensemble Regression
Consider a regression problem where there is no labeled data and the onl...
read it

Removal of Batch Effects using DistributionMatching Residual Networks
Sources of variability in experimentally derived data include measuremen...
read it

DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Network
Medical practitioners use survival models to explore and understand the ...
read it

A Deep Learning Approach to Unsupervised Ensemble Learning
We show how deep learning methods can be applied in the context of crowd...
read it

Unsupervised Ensemble Learning with Dependent Classifiers
In unsupervised ensemble learning, one obtains predictions from multiple...
read it

Estimating the Accuracies of Multiple Classifiers Without Labeled Data
In various situations one is given only the predictions of multiple clas...
read it

Ranking and combining multiple predictors without labeled data
In a broad range of classification and decision making problems, one is ...
read it