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Cristiano Leite de Castro
- ESANN 2024 - Unsupervised Drift Detection Using Quadtree Spatial Mapping [Details]
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- ESANN 2022 - High Accuracy and Low Regret for User-Cold-Start Using Latent Bandits [Details]
- No papers found
- ESANN 2019 - Tensor factorization to extract patterns in multimodal EEG data [Details]
- ESANN 2024 - Extrapolating Venusian Atmospheric Profiles using MAGMA Gaussian Processes [Details]
- ESANN 2023 - A hidden Markov model with Hawkes process-derived contextual variables to improve time series prediction. Case study in medical simulation. [Details]
- ESANN 2024 - LSTM encoder-decoder model for contextualized time series forecasting applied to the simulation of a digital patient's physiological variables. [Details]
- ESANN 2003 - Road Singularities Detection and Classification [Details]
- ESANN 2011 - Inferring the causal decomposition under the presence of deterministic relations [Details]
- ESANN 2008 - Do we need experts for time series forecasting? [Details]
- ESANN 1999 - Hidden Markov gating for prediction of change points in switching dynamical systems [Details]
- ESANN 2010 - Efficient online learning of a non-negative sparse autoencoder [Details]
- ESANN 2012 - Learning visuo-motor coordination for pointing without depth calculation [Details]
- ESANN 2013 - Neurally imprinted stable vector fields [Details]
- ESANN 2015 - A flat neural network architecture to represent movement primitives with integrated sequencing [Details]
- ESANN 2015 - An affinity matrix approach for structure selection of extreme learning machines [Details]
- ESANN 2014 - A new approach for multiple instance learning based on a homogeneity bag operator [Details]
- ESANN 2014 - Parameter-free regularization in Extreme Learning Machines with affinity matrices [Details]
- ESANN 2021 - A Multi-ELM Model for Incomplete Data [Details]
- ESANN 2021 - Machine Learning for Measuring and Analyzing Online Social Communications [Details]
- ESANN 2021 - NNBMSS: a Novel and Fast Method for Model Structure Selection [Details]
- ESANN 2024 - A Two-Stage Approach for Implicit Bias Detection in Generative Language Models [Details]
- ESANN 1998 - Forecasting time-series by Kohonen classification [Details]
- ESANN 1999 - Extraction of intrinsic dimension using CCA - Application to blind sources separation [Details]
- ESANN 2000 - A robust non-linear projection method [Details]
- ESANN 2000 - Time series forecasting using CCA and Kohonen maps - application to electricity consumption [Details]
- ESANN 2001 - Input data reduction for the prediction of financial time series [Details]
- ESANN 2002 - Curvilinear Distance Analysis versus Isomap [Details]
- ESANN 2002 - Width optimization of the Gaussian kernels in Radial Basis Function Networks [Details]
- ESANN 2003 - Fast approximation of the bootstrap for model selection [Details]
- ESANN 2004 - fast bootstrap for least-square support vector machines [Details]
- ESANN 2005 - Mutual information and gamma test for input selection [Details]
- ESANN 2005 - Pruned lazy learning models for time series prediction [Details]
- ESANN 2006 - Determination of the Mahalanobis matrix using nonparametric noise estimations [Details]
- ESANN 2006 - EM-algorithm for training of state-space models with application to time series prediction [Details]
- ESANN 2006 - LS-SVM functional network for time series prediction [Details]
- ESANN 2006 - Time series prediction using DirRec strategy [Details]
- ESANN 2007 - Nearest Neighbor Distributions and Noise Variance Estimation [Details]
- ESANN 2007 - SOM+EOF for finding missing values [Details]
- ESANN 2008 - A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM [Details]
- ESANN 2008 - Linear Projection based on Noise Variance Estimation - Application to Spectral Data [Details]
- ESANN 2008 - Using the Delta Test for Variable Selection [Details]
- ESANN 2009 - A faster model selection criterion for OP-ELM and OP-KNN: Hannan-Quinn criterion [Details]
- ESANN 2009 - Applying Mutual Information for Prototype or Instance Selection in Regression Problems [Details]
- ESANN 2009 - X-SOM and L-SOM: a nested approach for missing value imputation [Details]
- ESANN 2010 - Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs [Details]
- ESANN 2010 - Machine Learning Techniques based on Random Projections [Details]
- ESANN 2010 - Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs [Details]
- ESANN 2011 - Adaptive Kernel Smoothing Regression for Spatio-Temporal Environmental Datasets [Details]
- ESANN 2011 - Locating Anomalies Using Bayesian Factorizations and Masks [Details]
- ESANN 2012 - Relevance learning for time series inspection [Details]
- ESANN 2013 - Forecasting Financial Markets with Classified Tactical Signals [Details]
- ESANN 2013 - Visualizing dependencies of spectral features using mutual information [Details]
- ESANN 2014 - Finding Originally Mislabels with MD-ELM [Details]
- ESANN 2015 - Towards a Tomographic Index of Systemic Risk Measures [Details]
- ESANN 2017 - Advanced query strategies for Active Learning with Extreme Learning Machines [Details]
- ESANN 1995 - Performance analysis of a MLP weight initialization algorithm [Details]
- ESANN 2020 - A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction [Details]
- ESANN 2016 - Policy-gradient methods for Decision Trees [Details]
- ESANN 2005 - Artificial neural networks and prognosis in medicine. Survival analysis in breast cancer patients [Details]
- ESANN 2023 - Real-time Detection of Evoked Potentials by Deep Learning: a Case Study [Details]
- ESANN 2010 - Towards sub-quadratic learning of probability density models in the form of mixtures of trees [Details]
- ESANN 2015 - On the equivalence between regularized NMF and similarity-augmented graph partitioning [Details]
- ESANN 2017 - Learning human behaviors and lifestyle by capturing temporal relations in mobility patterns [Details]
- ESANN 2018 - Temporal modeling of ALS using longitudinal data and long-short term memory-based algorithm [Details]
- ESANN 1999 - A hybrid system for fraud detection in mobile communications [Details]
- ESANN 2006 - A survey of Sparse Component Analysis for blind source separation: principles, perspectives, and new challenges [Details]
- ESANN 2017 - Prediction of preterm infant mortality with Gaussian process classification [Details]
- ESANN 2022 - Tutorial - Continual Learning beyond classification [Details]
- ESANN 2024 - Continual Learning of Deep Neural Networks in The Age of Big Data [Details]
- No papers found