| Knowledge management and intellectual capital in knowledge-based organisations: a review and theoretical perspectives | 0 | 0.34 | 2020 |
| Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates | 11 | 0.50 | 2016 |
| Advances in learning analytics and educational data mining. | 0 | 0.34 | 2015 |
| Developments in computational intelligence and machine learning. | 1 | 0.36 | 2015 |
| Fully Empirical and Data-Dependent Stability-Based Bounds. | 13 | 0.49 | 2015 |
| Support Vector Machines And Strictly Positive Definite Kernel: The Regularization Hyperparameter Is More Important Than The Kernel Hyperparameters | 2 | 0.37 | 2015 |
| Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples. | 2 | 0.39 | 2015 |
| Human Algorithmic Stability and Human Rademacher Complexity. | 0 | 0.34 | 2015 |
| Model Selection for Big Data: Algorithmic Stability and Bag of Little Bootstraps on GPUs. | 0 | 0.34 | 2015 |
| Fast Convergence Of Extended Rademacher Complexity Bounds | 0 | 0.34 | 2015 |
| Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency. | 4 | 0.37 | 2015 |
| Shrinkage Learning To Improve Svm With Hints | 0 | 0.34 | 2015 |
| A Deep Connection Between the Vapnik-Chervonenkis Entropy and the Rademacher Complexity. | 2 | 0.40 | 2014 |
| Byte The Bullet: Learning on Real-World Computing Architectures. | 3 | 0.45 | 2014 |
| A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with a Digital Electronics Simulator | 2 | 0.39 | 2014 |
| Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions. | 9 | 0.55 | 2014 |
| Out-of-Sample Error Estimation: The Blessing of High Dimensionality | 1 | 0.34 | 2014 |
| Learning with few bits on small-scale devices: From regularization to energy efficiency. | 1 | 0.36 | 2014 |
| Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers | 9 | 0.45 | 2014 |
| Training Computationally Efficient SmartphoneBased Human Activity Recognition Models | 6 | 0.53 | 2013 |
| An improved analysis of the Rademacher data-dependent bound using its self bounding property. | 8 | 0.53 | 2013 |
| A Learning Machine with a Bit-Based Hypothesis Space. | 6 | 0.49 | 2013 |
| Human Activity and Motion Disorder Recognition: towards smarter Interactive Cognitive Environments. | 7 | 0.52 | 2013 |
| A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers | 0 | 0.34 | 2013 |
| Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector Regression | 24 | 1.54 | 2013 |
| Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity | 0 | 0.34 | 2013 |
| Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic. | 37 | 1.12 | 2013 |
| A Public Domain Dataset for Human Activity Recognition using Smartphones. | 132 | 3.86 | 2013 |
| In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine. | 10 | 0.51 | 2012 |
| Nested sequential minimal optimization for support vector machines | 3 | 0.40 | 2012 |
| Structural Risk Minimization and Rademacher Complexity for Regression. | 0 | 0.34 | 2012 |
| Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine | 164 | 5.75 | 2012 |
| In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines | 50 | 1.37 | 2012 |
| The `K' in K-fold Cross Validation. | 4 | 0.41 | 2012 |
| Rademacher complexity and structural risk minimization: an application to human gene expression datasets | 1 | 0.39 | 2012 |
| In-sample model selection for Support Vector Machines | 17 | 0.83 | 2011 |
| Maximal Discrepancy vs. Rademacher Complexity for error estimation. | 7 | 0.49 | 2011 |
| Selecting the hypothesis space for improving the generalization ability of Support Vector Machines. | 14 | 0.74 | 2011 |
| A FPGA Core Generator for Embedded Classification Systems | 14 | 0.74 | 2011 |
| The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers. | 15 | 0.70 | 2011 |
| Test error bounds for classifiers: A survey of old and new results | 2 | 0.39 | 2011 |
| Maximal Discrepancy for Support Vector Machines | 16 | 0.86 | 2010 |
| K-Fold Cross Validation for Error Rate Estimate in Support Vector Machines | 14 | 0.80 | 2009 |
| A support vector machine with integer parameters | 26 | 1.29 | 2008 |
| Smart plankton - a new generation of underwater wireless sensor network. | 0 | 0.34 | 2008 |
| Using Variable Neighborhood Search To Improve The Support Vector Machine Performance In Embedded Automotive Applications | 5 | 0.44 | 2008 |
| Smart Plankton: a Nature Inspired Underwater Wireless Sensor Network | 1 | 0.37 | 2008 |
| A Hardware-Friendly Support Vector Machine For Embedded Automotive Applications | 20 | 1.38 | 2007 |
| A learning machine for resource-limited adaptive hardware | 4 | 0.45 | 2007 |
