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Martin Bogdan
- ESANN 2023 - Is Boredom an Indicator on the way to Singularity of Artificial Intelligence? Hypotheses as Thought-Provoking Impulse [Details]
- ESANN 2023 - Sleep analysis in a CLIS patient using soft-clustering: a case study [Details]
- ESANN 2005 - Feature selection for high-dimensional industrial data [Details]
- ESANN 2006 - Artificial neural networks and machine learning for man-machine-interfaces - processing of nervous signals [Details]
- ESANN 2008 - Direct and inverse solution for a stimulus adaptation problem using SVR [Details]
- ESANN 2010 - Predicting spike-timing of a thalamic neuron using a stochastic synaptic model [Details]
- ESANN 2011 - Classifying mental states with machine learning algorithms using alpha activity decline [Details]
- ESANN 2012 - One Class SVM and Canonical Correlation Analysis increase performance in a c-VEP based Brain-Computer Interface (BCI) [Details]
- ESANN 2013 - Decoding stimulation intensity from evoked ECoG activity using support vector regression [Details]
- ESANN 2013 - Efficient prediction of x-axis intercepts of discrete impedance spectra [Details]
- ESANN 2017 - Collaborative filtering with neural networks [Details]
- ESANN 2018 - Neural Networks for Implicit Feedback Datasets [Details]
- ESANN 2021 - An Algorithmic Approach to Establish a Lower Bound for the Size of Semiring Neural Networks [Details]
- No papers found
- ESANN 2022 - Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features [Details]
- ESANN 2023 - Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection [Details]
- ESANN 2014 - Learning resets of neural working memory [Details]
- ESANN 2014 - Spiking AGREL [Details]
- ESANN 2014 - Spiking Neural Networks: Principles and Challenges [Details]
- ESANN 2002 - Modeling efficient conjunction detection with spiking neural networks [Details]
- ESANN 2000 - SpikeProp: backpropagation for networks of spiking neurons [Details]
- ESANN 2018 - Adaptive random forests for data stream regression [Details]
- ESANN 1999 - Development of a French speech recognizer using a hybrid HMM/MLP system [Details]
- ESANN 2001 - Relevance determination in Learning Vector Quantization [Details]
- ESANN 2003 - Monitoring technical systems with prototype based clustering [Details]
- ESANN 2021 - In-Station Train Movements Prediction: from Shallow to Deep Multi Scale Models [Details]
- ESANN 1993 - Mixture states in Potts neural networks [Details]
- ESANN 1993 - Paralell dynamics of extremely diluted neural networks [Details]
- ESANN 2006 - Fuzzy image segmentation with Fuzzy Labelled Neural Gas [Details]
- ESANN 2000 - Automatic detection of clustered microcalcifications in digital mammograms using an SVM classifier [Details]
- ESANN 2022 - Feature selection for transfer learning using particle swarm optimization and complexity measures [Details]
- ESANN 2022 - The role of feature selection in personalized recommender systems [Details]
- ESANN 2023 - Automated green machine learning for condition-based maintenance [Details]
- ESANN 2023 - Efficient feature selection for domain adaptation using Mutual Information Maximization [Details]
- ESANN 2023 - Green Machine Learning [Details]
- ESANN 2023 - Logarithmic division for green feature selection: an information-theoretic approach [Details]
- ESANN 2020 - Do we need hundreds of classifiers or a good feature selection? [Details]
- No papers found
- ESANN 2011 - Statistical dependence measure for feature selection in microarray datasets [Details]
- ESANN 2013 - A distributed wrapper approach for feature selection [Details]
- ESANN 2014 - Toward parallel feature selection from vertically partitioned data [Details]
- ESANN 2015 - Feature and kernel learning [Details]
- ESANN 2015 - Learning features on tear film lipid layer classification [Details]
- ESANN 2015 - On the use of machine learning techniques for the analysis of spontaneous reactions in automated hearing assessment [Details]
- ESANN 2016 - Data complexity measures for analyzing the effect of SMOTE over microarrays [Details]
- ESANN 2016 - Machine learning for medical applications [Details]
- ESANN 2016 - Using a feature selection ensemble on DNA microarray datasets [Details]
- ESANN 2017 - A distributed approach for classification using distance metrics [Details]
- ESANN 2017 - Algorithmic challenges in big data analytics [Details]
- ESANN 2018 - Analysis of imputation bias for feature selection with missing data [Details]
- ESANN 2000 - Application of MLP and stochastic simulations for electricity load forecasting in Russia [Details]
- ESANN 2020 - Estimating Individual Treatment Effects through Causal Populations Identification [Details]
- ESANN 1998 - NAR time-series prediction: a Bayesian framework and an experiment [Details]
- ESANN 2000 - An algorithm for the addition of time-delayed connections to recurrent neural networks [Details]
- ESANN 2020 - Graph Neural Networks for the Prediction of Protein-Protein Interfaces [Details]
- ESANN 2022 - A weakly supervised approach to skin lesion segmentation [Details]
- ESANN 2022 - Deep Learning Approaches for mice glomeruli segmentation [Details]
- ESANN 2008 - Multilayer perceptron to model the decarburization process in stainless steel production [Details]
- No papers found
- ESANN 2022 - Lightening CNN architectures by regularization driven weights' pruning [Details]
- ESANN 2024 - Vision Language Models as Policy Learners in Reinforcement Learning Environments [Details]
- No papers found
- ESANN 2019 - Active one-shot learning with Prototypical Networks [Details]
- No papers found