
Improving Approximate Optimal Transport Distances using Quantization
Optimal transport (OT) is a popular tool in machine learning to compare ...
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Entropic Causal Inference: Identifiability and Finite Sample Results
Entropic causal inference is a framework for inferring the causal direct...
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kVariance: A Clustered Notion of Variance
We introduce kvariance, a generalization of variance built on the machi...
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HighDimensional Feature Selection for Sample Efficient Treatment Effect Estimation
The estimation of causal treatment effects from observational data is a ...
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Active Structure Learning of Causal DAGs via Directed Clique Tree
A growing body of work has begun to study intervention design for effici...
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The Computational Limits of Deep Learning
Deep learning's recent history has been one of achievement: from triumph...
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GaussianSmooth Optimal Transport: Metric Structure and Statistical Efficiency
Optimal transport (OT), and in particular the Wasserstein distance, has ...
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Statistical Model Aggregation via Parameter Matching
We consider the problem of aggregating models learned from sequestered, ...
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Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity
With the recent evolution of mobile health technologies, health scientis...
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BreGMN: scaledBregman Generative Modeling Networks
The family of fdivergences is ubiquitously applied to generative modeli...
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Convergence of Smoothed Empirical Measures with Applications to Entropy Estimation
This paper studies convergence of empirical measures smoothed by a Gauss...
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Bayesian Nonparametric Federated Learning of Neural Networks
In federated learning problems, data is scattered across different serve...
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Estimating Differential Entropy under Gaussian Convolutions
This paper studies the problem of estimating the differential entropy h(...
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Estimating Information Flow in Neural Networks
We study the flow of information and the evolution of internal represent...
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Timedependent spatially varying graphical models, with application to brain fMRI data analysis
In this work, we present an additive model for spacetime data that spli...
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Action Centered Contextual Bandits
Contextual bandits have become popular as they offer a middle ground bet...
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Similarity Function Tracking using Pairwise Comparisons
Recent work in distance metric learning has focused on learning transfor...
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Nonstationary Distance Metric Learning
Recent work in distance metric learning has focused on learning transfor...
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Detection of Anomalous Crowd Behavior Using SpatioTemporal Multiresolution Model and Kronecker Sum Decompositions
In this work we consider the problem of detecting anomalous spatiotempo...
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Kronecker Sum Decompositions of SpaceTime Data
In this paper we consider the use of the space vs. time Kronecker produc...
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Kristjan Greenewald
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