Lista de obras - Davide Anguita - Dominio Público Uruguay

A Deep Connection Between the Vapnik–Chervonenkis Entropy and the Rademacher Complexity

artículo científico publicado en 2014

A Learning Analytics Approach to Correlate the Academic Achievements of Students with Interaction Data from an Educational Simulator

A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with a Digital Electronics Simulator

A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers

A local Vapnik-Chervonenkis complexity.

artículo científico publicado en 2016

A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space

scholarly article published August 2013

A support vector machine with integer parameters

An improved analysis of the Rademacher data-dependent bound using its self bounding property

artículo científico publicado en 2013

Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf

Can machine learning explain human learning?

scholarly article by Mehrnoosh Vahdat et al published June 2016 in Neurocomputing

Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector Regression

Fast convergence of extended Rademacher Complexity bounds

Feed-forward support vector machine without multipliers.

artículo científico publicado en 2006

Fully Empirical and Data-Dependent Stability-Based Bounds

artículo científico publicado en 2014

Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates

Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine

artículo científico publicado en 2012

Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions

Improved neural network for SVM learning

artículo científico publicado en 2002

In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine

In-sample and out-of-sample model selection and error estimation for support vector machines

artículo científico publicado en 2012

In-sample model selection for Support Vector Machines

article

Learning Hardware-Friendly Classifiers Through Algorithmic Stability

Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency

article

Learning algorithm for nonlinear support vector machines suited for digital VLSI

artículo científico publicado en 1999

Local Rademacher Complexity: sharper risk bounds with and without unlabeled samples

artículo científico publicado en 2015

Long-term energy load forecasting using Auto-Regressive and approximating Support Vector Regression

Machine learning approaches for improving condition-based maintenance of naval propulsion plants

article

Machine learning for wear forecasting of naval assets for condition-based maintenance applications

scholarly article published March 2015

Maximal Discrepancy for Support Vector Machines

Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory

article

Nested Sequential Minimal Optimization for Support Vector Machines

Out-of-Sample Error Estimation: The Blessing of High Dimensionality

PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis

scholarly article by Luca Oneto et al published September 2016 in Pattern Recognition Letters

Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets

article

Randomized learning: Generalization performance of old and new theoretically grounded algorithms

Selecting the hypothesis space for improving the generalization ability of Support Vector Machines

Ship efficiency forecast based on sensors data collection: Improving numerical models through data analytics

Shrinkage learning to improve SVM with hints

Smart underwater wireless sensor networks

Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities

article published in 2014

Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity

Statistical Learning Theory and ELM for Big Social Data Analysis

article

Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters

Test error bounds for classifiers: A survey of old and new results

Tikhonov, Ivanov and Morozov regularization for support vector machine learning

scholarly article by Luca Oneto et al published 22 December 2015 in Machine Learning

Training Computationally Efficient Smartphone–Based Human Activity Recognition Models

artículo científico publicado en 2013

Transition-Aware Human Activity Recognition Using Smartphones

artículo científico publicado en 2016

Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers

scholarly article by Davide Anguita et al published February 2014 in Pattern Recognition Letters

Using Variable Neighborhood Search to improve the Support Vector Machine performance in embedded automotive applications

Using unsupervised analysis to constrain generalization bounds for support vector classifiers.

artículo científico publicado en 2010

Lista de obras de Davide Anguita

A Deep Connection Between the Vapnik–Chervonenkis Entropy and the Rademacher Complexity

A Learning Analytics Approach to Correlate the Academic Achievements of Students with Interaction Data from an Educational Simulator

A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with a Digital Electronics Simulator

A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers

A local Vapnik-Chervonenkis complexity.

A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space

A support vector machine with integer parameters

An improved analysis of the Rademacher data-dependent bound using its self bounding property

Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf

Can machine learning explain human learning?

Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector Regression

Fast convergence of extended Rademacher Complexity bounds

Feed-forward support vector machine without multipliers.

Fully Empirical and Data-Dependent Stability-Based Bounds

Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates

Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine

Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions

Improved neural network for SVM learning

In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine

In-sample and out-of-sample model selection and error estimation for support vector machines

In-sample model selection for Support Vector Machines

Learning Hardware-Friendly Classifiers Through Algorithmic Stability

Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency

Learning algorithm for nonlinear support vector machines suited for digital VLSI

Local Rademacher Complexity: sharper risk bounds with and without unlabeled samples

Long-term energy load forecasting using Auto-Regressive and approximating Support Vector Regression

Machine learning approaches for improving condition-based maintenance of naval propulsion plants

Machine learning for wear forecasting of naval assets for condition-based maintenance applications

Maximal Discrepancy for Support Vector Machines

Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory

Nested Sequential Minimal Optimization for Support Vector Machines

Out-of-Sample Error Estimation: The Blessing of High Dimensionality

PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis

Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets

Randomized learning: Generalization performance of old and new theoretically grounded algorithms

Selecting the hypothesis space for improving the generalization ability of Support Vector Machines

Ship efficiency forecast based on sensors data collection: Improving numerical models through data analytics

Shrinkage learning to improve SVM with hints

Smart underwater wireless sensor networks

Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities

Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity

Statistical Learning Theory and ELM for Big Social Data Analysis

Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters

Test error bounds for classifiers: A survey of old and new results

Tikhonov, Ivanov and Morozov regularization for support vector machine learning

Training Computationally Efficient Smartphone–Based Human Activity Recognition Models

Transition-Aware Human Activity Recognition Using Smartphones

Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers

Using Variable Neighborhood Search to improve the Support Vector Machine performance in embedded automotive applications

Using unsupervised analysis to constrain generalization bounds for support vector classifiers.