Publications related to Comparing molecules and solids across structural and alchemical space

Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

Anatole von Lilienfeld, Nicholas John Browning

The training of molecular models of quantum mechanical properties based on statistical machine learning requires large data sets which exemplify the map from chemical structure to molecular property. Intelligent a priori selection of training examples is o ...

2017

Smoothing technique for nonsmooth composite minimization with linear operator

Volkan Cevher, Van Quang Nguyen

We introduce and analyze an algorithm for the minimization of convex functions that are the sum of differentiable terms and proximable terms composed with linear operators. The method builds upon the recently developed smoothed gap technique. In addition t ...

2017

Soft-Sphere Continuum Solvation in Electronic-Structure Calculations

Nicola Marzari, Oliviero Andreussi

We present an implicit solvation approach where the interface-between the quantum-mechanical solute and the surrounding environment is, described by a fully continuous permittivity built up with atomic-centered "soft" spheres. This approach combines many o ...

Amer Chemical Soc2017

An Equivalence between the Lasso and Support Vector Machines

Martin Jaggi

We investigate the relation of two fundamental tools in machine learning and signal processing, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression. We show that the resulting optimization problems are eq ...

Chapman and Hall/CRC2014

Hydraulic-hydrologic model for the Zambezi River using satellite data and artificial intelligence techniques

José Pedro Gamito de Saldanha Calado Matos

The development of hydraulic-hydrologic models is a challenge in the case of large catchment areas with scarce or erroneous measurement data and observations. With his study Mr. Dr. José Pedro Matos made several original contributions in order to overcome ...

EPFL - LCH2014

Prediction of surface temperature in lakes with different morphology using air temperature

Alfred Johny Wüest, Sebastiano Piccolroaz, Marco Toffolon, Martin Schmid

Temperature of the surface layer of temperate lakes is reconstructed by means of a simplified model on the basis of air temperature alone. The comparison between calculated and observed data shows a remarkable agreement (Nash-Sutcliffe efficiency indices a ...

Amer Soc Limnology Oceanography2014

Self-consistent continuum solvation (SCCS): The case of charged systems

Nicola Marzari, Oliviero Andreussi

The recently developed self-consistent continuum solvation model (SCCS) [O. Andreussi, I. Dabo, and N. Marzari, J. Chem. Phys. 136, 064102 (2012)] is applied here to charged species in aqueous solutions. Describing ions in solution represents a great chall ...

Amer Inst Physics2013

Compressible distributions for high-dimensional statistics

Volkan Cevher, Rémi Gribonval

We develop a principled way of identifying probability distributions whose independent and identically distributed realizations are compressible, i.e., can be well approximated as sparse. We focus on Gaussian compressed sensing, an example of underdetermin ...

Institute of Mathematical Statistics2012

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Volkan Cevher, Anastasios Kyrillidis

The least absolute shrinkage and selection operator (LASSO) for linear regression exploits the geometric interplay of the

\ell_2

-data error objective and the

\ell_1

-norm constraint to arbitrarily select sparse models. Guiding this uninformed selection ...

IEEE2012

Chebyshev polynomial approximation for transductive learning on graphs

Nathanaël Perraudin

The goal of transductive learning is to find a way to recover the labels of lots of data with only a few known samples. In this work, we will work on graphs for two reasons. First, it’s possible to construct a graph from a given dataset with features. The ...

2011

Comparing molecules and solids across structural and alchemical space

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Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

Smoothing technique for nonsmooth composite minimization with linear operator

Soft-Sphere Continuum Solvation in Electronic-Structure Calculations

An Equivalence between the Lasso and Support Vector Machines

Hydraulic-hydrologic model for the Zambezi River using satellite data and artificial intelligence techniques

Prediction of surface temperature in lakes with different morphology using air temperature

Self-consistent continuum solvation (SCCS): The case of charged systems

Compressible distributions for high-dimensional statistics

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Chebyshev polynomial approximation for transductive learning on graphs

Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

Soft-Sphere Continuum Solvation in Electronic-Structure Calculations

Smoothing technique for nonsmooth composite minimization with linear operator

Self-consistent continuum solvation (SCCS): The case of charged systems

An Equivalence between the Lasso and Support Vector Machines

Hydraulic-hydrologic model for the Zambezi River using satellite data and artificial intelligence techniques

Prediction of surface temperature in lakes with different morphology using air temperature

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Compressible distributions for high-dimensional statistics

Chebyshev polynomial approximation for transductive learning on graphs