Publications related to Generalization error

Structured Dimensionality Reduction for Additive Model Regression

Additive models are regression methods which model the response variable as the sum of univariate transfer functions of the input variables. Key benefits of additive models are their accuracy and interpretability on many real-world tasks. Additive models a ...

Institute of Electrical and Electronics Engineers2016

Ask Erno: a self-learning tool for assignment and prediction of nuclear magnetic resonance spectra

Luc Patiny, Julien Wist, Andrés Mauricio Castillo Robles

Background: We present "Ask Erno", a self-learning system for the automatic analysis of NMR spectra, consisting of integrated chemical shift assignment and prediction tools. The output of the automatic assignment component initializes and improves a databa ...

Biomed Central Ltd2016

Estimation Error of the Constrained Lasso

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

This paper presents a non-asymptotic upper bound for the estimation error of the constrained lasso, under the high-dimensional (

n \ll p

) setting. In contrast to existing results, the error bound in this paper is sharp, is valid when the parameter to be e ...

2016

Reconstruction of Finite Rate of Innovation Signals with Model-Fitting Approach

Dimitri Nestor Alice Van De Ville, Thierry Blu, Zafer Dogan

Finite rate of innovation (FRI) is a recent framework for sampling and reconstruction of a large class of parametric signals that are characterized by finite number of innovations (parameters) per unit interval. In the absence of noise, exact recovery of F ...

Institute of Electrical and Electronics Engineers2015

A statistical shape model of the human second cervical vertebra

Simon Nessim Henein, Charles Baur, Marine Chantal Elisabeth Geneviève Clogenson, Reto Meuli

Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) ...

Springer Heidelberg2015

Distributed Policy Evaluation Under Multiple Behavior Strategies

Ali H. Sayed

We apply diffusion strategies to develop a fully-distributed cooperative reinforcement learning algorithm in which agents in a network communicate only with their immediate neighbors to improve predictions about their environment. The algorithm can also be ...

IEEE2015

Beyond Knowledge Tracing. Modeling Skill Topologies with Bayesian Networks

Modeling and predicting student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for student modeling is Bayesian Knowledge Tracing (BKT). BKT models, however, lack the ability to describe the hierarchy and relationship ...

Springer2014

A Probabilistic Approach to Mining Mobile Phone Data Sequences

Daniel Gatica-Perez, Katayoun Farrahi

We present a new approach to address the problem of large sequence mining from big data. The particular problem of interest is the effective mining of long sequences from large-scale location data to be practical for Reality Mining applications, which suff ...

2014

A Sequential Topic Model for Mining Recurrent Activities from Long Term Video Logs

Jean-Marc Odobez, Rémi Emonet, Jagannadan Varadarajan

This paper introduces a novel probabilistic activity modeling approach that mines recurrent sequential patterns called motifs from documents given as word×time count matrices (e.g., videos). In this model, documents are represented as a mixture of sequenti ...

Springer2013

Stability and Hypothesis Transfer Learning

Ilja Kuzborskij

We consider the transfer learning scenario, where the learner does not have access to the source domain directly, but rather operates on the basis of hypotheses induced from it - the Hypothesis Transfer Learning (HTL) problem. Particularly, we conduct a th ...

2013

Generalization error

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Structured Dimensionality Reduction for Additive Model Regression

Ask Erno: a self-learning tool for assignment and prediction of nuclear magnetic resonance spectra

Estimation Error of the Constrained Lasso

Reconstruction of Finite Rate of Innovation Signals with Model-Fitting Approach

A statistical shape model of the human second cervical vertebra

Distributed Policy Evaluation Under Multiple Behavior Strategies

Beyond Knowledge Tracing. Modeling Skill Topologies with Bayesian Networks

A Probabilistic Approach to Mining Mobile Phone Data Sequences

A Sequential Topic Model for Mining Recurrent Activities from Long Term Video Logs

Stability and Hypothesis Transfer Learning

Beyond Knowledge Tracing. Modeling Skill Topologies with Bayesian Networks

Structured Dimensionality Reduction for Additive Model Regression

A statistical shape model of the human second cervical vertebra

A Sequential Topic Model for Mining Recurrent Activities from Long Term Video Logs

Reconstruction of Finite Rate of Innovation Signals with Model-Fitting Approach

Estimation Error of the Constrained Lasso

A Probabilistic Approach to Mining Mobile Phone Data Sequences

Distributed Policy Evaluation Under Multiple Behavior Strategies

Stability and Hypothesis Transfer Learning

Ask Erno: a self-learning tool for assignment and prediction of nuclear magnetic resonance spectra