
Prediction of Spatial Point Processes: Regularized Method with OutofSample Guarantees
A spatial point process can be characterized by an intensity function wh...
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Learning Robust Decision Policies from Observational Data
We address the problem of learning a decision policy from observational ...
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A latent variable approach to heat load prediction in thermal grids
In this paper a new method for heat load prediction in district energy s...
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Robust Prediction when Features are Missing
Predictors are learned using past training data containing features whic...
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Calibration tests in multiclass classification: A unifying framework
In safetycritical applications a probabilistic model is usually require...
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Robust Risk Minimization for Statistical Learning
We consider a general statistical learning problem where an unknown frac...
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Effect Inference from TwoGroup Data with Sampling Bias
In many applications, different populations are compared using data that...
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Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding
We address the problem of inferring the causal effect of an exposure on ...
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Robust SemiSupervised Learning when Labels are Missing at Random
Semisupervised learning methods are motivated by the relative paucity o...
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Data Consistency Approach to Model Validation
In scientific inference problems, the underlying statistical modeling as...
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Learning Localized SpatioTemporal Models From Streaming Data
We address the problem of predicting spatiotemporal processes with temp...
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Composite Gaussian Processes: Scalable Computation and Performance Analysis
Gaussian process (GP) models provide a powerful tool for prediction but ...
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Learning Sparse Graphs for Prediction and Filtering of Multivariate Data Processes
We address the problem of prediction and filtering of multivariate data ...
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How consistent is my model with the data? InformationTheoretic Model Check
The choice of model class is fundamental in statistical learning and sys...
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Is My Model Flexible Enough? InformationTheoretic Model Check
The choice of model class is fundamental in statistical learning and sys...
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ModelRobust Counterfactual Prediction Method
We develop a method for assessing counterfactual predictions with multip...
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Online Learning for DistributionFree Prediction
We develop an online learning method for prediction, which is important ...
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Recursive nonlinearsystem identification using latent variables
In this paper we develop a method for learning nonlinear systems with mu...
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Prediction performance after learning in Gaussian process regression
This paper considers the quantification of the prediction performance in...
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Dave Zachariah
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