Concept

Nonparametric regression

Related publications (128)

From averaging to acceleration, there is only a step-size

We consider the optimization of a quadratic objective function whose gradients are only accessible through a stochastic oracle that returns the gradient at any given point plus a zero-mean finite variance random error. We present the first algorithm that a ...

2015

A Geometric View on Constrained M-Estimators

Volkan Cevher, Yen-Huan Li, Ya-Ping Hsieh, Nissim Zerbib

We study the estimation error of constrained M-estimators, and derive explicit upper bounds on the expected estimation error determined by the Gaussian width of the constraint set. Both of the cases where the true parameter is on the boundary of the constr ...

2015

Process Design and Optimization (MLS-S03): a Journey in Modeling, Optimization and Regression

Julien Léo Billeter

This lecture describes the following topics: • Preamble on Linear Algebra • Dynamic and Static Models • Solving Dynamic and Static Models • Solving Optimization Problems • Solving Regression Problems ...

2015

Heat demand estimation for different building types at regional scale considering building parameters and urban topography

François Maréchal, Jessen Page, Nils Christian Schüler, Alexandre Suzanne Jean-Marie Bertrand

This study aims towards an improved estimation of annual heat demand of the building stock for an entire region. This requires the holistic representation of aspects influencing the heat demand of buildings, namely their geometry, fabric, users and surroun ...

Elsevier2015

Interactive Design of Probability Density Functions for Shape Grammars

Mark Pauly, Duygu Ceylan, Boris Neubert, Stefan Lienhard

A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density function (p ...

Assoc Computing Machinery2015

A comparison of strategies for estimation of ultrafine particle number concentrations in urban air pollution monitoring networks

Matteo Reggente, Prashant Kumar

We propose three estimation strategies (local, remote and mixed) for ultrafine particles (UFP) at three sites in an urban air pollution monitoring network. Estimates are obtained through Gaussian process regression based on concentrations of gaseous pollut ...

Elsevier Sci Ltd2015

Forecasting price spikes in European day-ahead electricity markets using decision trees

Anna Fragkioudaki

Although the techniques for normal price prediction are well advanced, price spike prediction remains a challenge. The aim of this paper is to present a method to predict both normal day-ahead electricity prices as well as day-ahead price spikes using clas ...

IEEE2015

Consistency of $\ell_1$-Regularized Maximum-Likelihood for Compressive Poisson Regression

Volkan Cevher, Yen-Huan Li

We consider Poisson regression with the canonical link function. This regression model is widely used in regression analysis involving count data; one important application in electrical engineering is transmission tomography. In this paper, we establish t ...

2015

Additive Smooth Modelling with Splines

Thomas Lugrin

Linear regression summarises the link between a variable of interest and one or several explanatory variables through a parametric relationship. Hastie and Tibshirani (1986) extended this approach by allowing a non-parametric description of the dependence ...

2014

A new model for TBM performance prediction in blocky rock conditions

Jian Zhao, Andrea Delisio

The term "blocky rock conditions" is generally associated with face instabilities in blocky/jointed rock masses. These events are generally promoted by unfavorable rock mass structural conditions, in terms of joint frequency and orientation, and acting str ...

Pergamon-Elsevier Science Ltd2014

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