
Leveraging Expert Consistency to Improve Algorithmic Decision Support
Due to their promise of superior predictive power relative to human asse...
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SelfReflective Variational Autoencoder
The Variational Autoencoder (VAE) is a powerful framework for learning p...
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Preferencebased Reinforcement Learning with FiniteTime Guarantees
Preferencebased Reinforcement Learning (PbRL) replaces reward values in...
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SystemLevel Predictive Maintenance: Review of Research Literature and Gap Analysis
This paper reviews current literature in the field of predictive mainten...
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Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing Risks
We describe a new approach to estimating relative risks in timetoevent...
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Pairwise Feedback for Data Programming
The scalability of the labeling process and the attainable quality of la...
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Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning
Monitoring physiological responses to hemodynamic stress can help in det...
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Zeroth Order Nonconvex optimization with DuelingChoice Bandits
We consider a novel setting of zeroth order nonconvex optimization, whe...
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Active Learning for Graph Neural Networks via Node Feature Propagation
Graph Neural Networks (GNNs) for prediction tasks like node classificati...
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Thresholding Bandit Problem with Both Duels and Pulls
The Thresholding Bandit Problem (TBP) aims to find the set of arms with ...
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Nonlinear SemiParametric Models for Survival Analysis
Semiparametric survival analysis methods like the Cox Proportional Haza...
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Double Adaptive Stochastic Gradient Optimization
Adaptive moment methods have been remarkably successful in deep learning...
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Dependency Leakage: Analysis and Scalable Estimators
In this paper, we prove the first theoretical results on dependency leak...
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Learning under selective labels in the presence of expert consistency
We explore the problem of learning under selective labels in the context...
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Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
In supervised learning, we leverage a labeled dataset to design methods ...
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Novel Prediction Techniques Based on Clusterwise Linear Regression
In this paper we explore different regression models based on Clusterwis...
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Discovery of Complex Anomalous Patterns of Sexual Violence in El Salvador
When sexual violence is a product of organized crime or social imaginary...
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Learning Mixtures of MultiOutput Regression Models by Correlation Clustering for MultiView Data
In many datasets, different parts of the data may have their own pattern...
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Scaling Active Search using Linear Similarity Functions
Active Search has become an increasingly useful tool in information retr...
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NoiseTolerant Interactive Learning from Pairwise Comparisons
We study the problem of interactively learning a binary classifier using...
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Clustering on the Edge: Learning Structure in Graphs
With the recent popularity of graphical clustering methods, there has be...
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Canonical Autocorrelation Analysis
We present an extension of sparse Canonical Correlation Analysis (CCA) d...
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Lass0: sparse nonconvex regression by local search
We compute approximate solutions to L0 regularized linear regression usi...
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Performance Bounds for Pairwise Entity Resolution
One significant challenge to scaling entity resolution algorithms to mas...
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Artur Dubrawski
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