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06/05/2023
Optimal transport for automatic alignment of untargeted metabolomic data
Untargeted metabolomic profiling through liquid chromatography-mass spec...
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01/05/2023
On the Approximation Accuracy of Gaussian Variational Inference
The main quantities of interest in Bayesian inference are arguably the f...
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01/04/2023
Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow
Gaussian mixture models form a flexible and expressive parametric family...
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10/26/2022
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery
We revisit the problem of recovering a low-rank positive semidefinite ma...
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10/12/2022
GULP: a prediction-based metric between representations
Comparing the representations learned by different neural networks has r...
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06/27/2022
On the sample complexity of entropic optimal transport
We study the sample complexity of entropic optimal transport in high dim...
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05/31/2022
Variational inference via Wasserstein gradient flows
Along with Markov chain Monte Carlo (MCMC) methods, variational inferenc...
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02/15/2022
An algorithmic solution to the Blotto game using multi-marginal couplings
We describe an efficient algorithm to compute solutions for the general ...
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11/19/2021
Gaussian Determinantal Processes: a new model for directionality in data
Determinantal point processes (a.k.a. DPPs) have recently become popular...
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09/17/2021
Gaussian discrepancy: a probabilistic relaxation of vector balancing
We introduce a novel relaxation of combinatorial discrepancy called Gaus...
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08/12/2021
An Optimal Transport Approach to Causal Inference
We propose a method based on optimal transport theory for causal inferen...
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06/24/2021
Multi-Reference Alignment for sparse signals, Uniform Uncertainty Principles and the Beltway Problem
Motivated by cutting-edge applications like cryo-electron microscopy (cr...
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05/29/2021
Rejection sampling from shape-constrained distributions in sublinear time
We consider the task of generating exact samples from a target distribut...
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05/29/2021
The query complexity of sampling from strongly log-concave distributions in one dimension
We establish the first tight lower bound of Ω(loglogκ) on the query comp...
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12/23/2020
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm
Conventional wisdom in the sampling literature, backed by a popular diff...
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11/10/2020
Efficient Interpolation of Density Estimators
We study the problem of space and time efficient evaluation of a nonpara...
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11/10/2020
A Statistical Perspective on Coreset Density Estimation
Coresets have emerged as a powerful tool to summarize data by selecting ...
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10/22/2020
Fast and Smooth Interpolation on Wasserstein Space
We propose a new method for smoothly interpolating probability measures ...
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06/13/2020
Optimal Rates for Estimation of Two-Dimensional Totally Positive Distributions
We study minimax estimation of two-dimensional totally positive distribu...
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06/03/2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
Stein Variational Gradient Descent (SVGD), a popular sampling algorithm,...
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05/24/2020
Projection to Fairness in Statistical Learning
In the context of regression, we consider the fundamental question of ma...
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05/19/2020
Exponential ergodicity of mirror-Langevin diffusions
Motivated by the problem of sampling from ill-conditioned log-concave di...
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01/06/2020
Gradient descent algorithms for Bures-Wasserstein barycenters
We study first order methods to compute the barycenter of a probability ...
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10/30/2019
Balancing Gaussian vectors in high dimension
Motivated by problems in controlled experiments, we study the discrepanc...
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10/28/2019
Power analysis of knockoff filters for correlated designs
The knockoff filter introduced by Barber and Candès 2016 is an elegant f...
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09/16/2019
Estimation of Wasserstein distances in the Spiked Transport Model
We propose a new statistical model, the spiked transport model, which fo...
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08/02/2019
Fast convergence of empirical barycenters in Alexandrov spaces and the Wasserstein space
This work establishes fast rates of convergence for empirical barycenter...
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06/08/2019
Estimation Rates for Sparse Linear Cyclic Causal Models
Causal models are important tools to understand complex phenomena and pr...
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05/14/2019
Minimax rates of estimation for smooth optimal transport maps
Brenier's theorem is a cornerstone of optimal transport that guarantees ...
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04/05/2019
Estimation of Monge Matrices
Monge matrices and their permuted versions known as pre-Monge matrices n...
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09/14/2018
Entropic optimal transport is maximum-likelihood deconvolution
We give a statistical interpretation of entropic optimal transport by sh...
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06/27/2018
Uncoupled isotonic regression via minimum Wasserstein deconvolution
Isotonic regression is a standard problem in shape-constrained estimatio...
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06/19/2018
Statistical Optimal Transport via Geodesic Hubs
We propose a new method to estimate Wasserstein distances and optimal tr...
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04/02/2018
Sparse Gaussian ICA
Independent component analysis (ICA) is a cornerstone of modern data ana...
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02/25/2018
Teacher Improves Learning by Selecting a Training Subset
We call a learner super-teachable if a teacher can trim down an iid trai...
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10/28/2017
Minimax Rates and Efficient Algorithms for Noisy Sorting
There has been a recent surge of interest in studying permutation-based ...
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05/26/2017
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Computing optimal transport distances such as the earth mover's distance...
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07/08/2016
Optimal Rates of Statistical Seriation
Given a matrix the seriation problem consists in permuting its rows in s...
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11/18/2015
Online learning in repeated auctions
Motivated by online advertising auctions, we consider repeated Vickrey a...
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04/03/2013
Computational Lower Bounds for Sparse PCA
In the context of sparse principal component detection, we bring evidenc...
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02/06/2013
Bounded regret in stochastic multi-armed bandits
We study the stochastic multi-armed bandit problem when one knows the va...
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03/12/2012
Deviation optimal learning using greedy Q-aggregation
Given a finite family of functions, the goal of model selection aggregat...
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02/23/2012
Optimal detection of sparse principal components in high dimension
We perform a finite sample analysis of the detection levels for sparse p...
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10/27/2011
The multi-armed bandit problem with covariates
We consider a multi-armed bandit problem in a setting where each arm pro...
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02/28/2011
Neyman-Pearson classification, convexity and stochastic constraints
Motivated by problems of anomaly detection, this paper implements the Ne...
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11/16/2009
