A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z
Jumutc Vilen
- ESANN 2014 - Reweighted l1 Dual Averaging Approach for Sparse Stochastic Learning [Details]
- ESANN 2005 - Support Vector Machine For Functional Data Classification [Details]
- ESANN 2007 - Clustering a medieval social network by SOM using a kernel based distance measure [Details]
- ESANN 2008 - Consistency of Derivative Based Functional Classifiers on Sampled Data [Details]
- ESANN 2009 - Topologically Ordered Graph Clustering via Deterministic Annealing [Details]
- ESANN 2013 - Multiple Kernel Self-Organizing Maps [Details]
- ESANN 2017 - Accelerating stochastic kernel SOM [Details]
- ESANN 2004 - BIOSEG: a bioinspired vlsi analog system for image segmentation [Details]
- ESANN 2005 - Exponential stability of implicit Euler, discrete-time Hopfield neural networks [Details]
- ESANN 2002 - Searching for the embedded manifolds in high-dimensional data, problems and unsolved questions [Details]
- ESANN 1997 - Measuring topology preservation in maps of real-world data [Details]
- ESANN 1998 - Magnification control in neural maps [Details]
- ESANN 1999 - Benefits and limits of the self-organizing map and its variants in the area of satellite remote sensoring processing [Details]
- ESANN 2000 - Neural networks approaches in medicine - a review of actual developments [Details]
- ESANN 2001 - Evolutionary algorithms and neural networks in hybrid systems [Details]
- ESANN 2001 - Input pruning for neural gas architectures [Details]
- ESANN 2002 - Batch-RLVQ [Details]
- ESANN 2002 - Exploratory Data Analysis in Medicine and Bioinformatics [Details]
- ESANN 2003 - Magnification Control in Winner Relaxing Neural Gas [Details]
- ESANN 2003 - Mathematical Aspects of Neural Networks [Details]
- ESANN 2020 - Quantum-Inspired Learning Vector Quantization for Classification Learning [Details]
- ESANN 2021 - RecLVQ: Recurrent Learning Vector Quantization [Details]
- ESANN 2021 - The Coming of Age of Interpretable and Explainable Machine Learning Models [Details]
- ESANN 2021 - The LVQ-based Counter Propagation Network -- an Interpretable Information Bottleneck Approach [Details]
- ESANN 2022 - Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features [Details]
- ESANN 2022 - Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine [Details]
- ESANN 2023 - Learning Vector Quantization in Context of Information Bottleneck Theory [Details]
- ESANN 2023 - Quantum Artificial Intelligence: A tutorial [Details]
- ESANN 2023 - Quantum-ready vector quantization: Prototype learning as a binary optimization problem [Details]
- ESANN 2023 - Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection [Details]
- ESANN 2023 - Variants of Neural Gas for Regression Learning [Details]
- ESANN 2024 - About Vector Quantization and its Privacy in Federated Learning [Details]
- ESANN 2024 - Domain Knowledge Integration in Machine Learning Systems - An Introduction [Details]
- ESANN 2020 - Quantum-Inspired Learning Vector Quantization for Classification Learning [Details]
- ESANN 2004 - Theory and applications of neural maps [Details]
- ESANN 2005 - Classification using non-standard metrics [Details]
- ESANN 2005 - Generalized Relevance LVQ with Correlation Measures for Biological Data [Details]
- ESANN 2005 - Relevance learning for mental disease classification [Details]
- ESANN 2006 - Fuzzy image segmentation with Fuzzy Labelled Neural Gas [Details]
- ESANN 2006 - Magnification control for batch neural gas [Details]
- ESANN 2006 - Margin based Active Learning for LVQ Networks [Details]
- ESANN 2006 - Neural networks and machine learning in bioinformatics - theory and applications [Details]
- ESANN 2007 - How to process uncertainty in machine learning? [Details]
- ESANN 2007 - Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS [Details]
- ESANN 2008 - Generalized matrix learning vector quantizer for the analysis of spectral data [Details]
- ESANN 2008 - Machine learning approches and pattern recognition for spectral data [Details]
- ESANN 2008 - Magnification Control in Relational Neural Gas [Details]
- ESANN 2008 - Metric adaptation for supervised attribute rating [Details]
- ESANN 2009 - Fuzzy Fleiss-kappa for Comparison of Fuzzy Classifiers [Details]
- ESANN 2009 - Median Variant of Fuzzy c-Means [Details]
- ESANN 2009 - Neural Maps and Learning Vector Quantization - Theory and Applications [Details]
- ESANN 2010 - Divergence based Learning Vector Quantization [Details]
- ESANN 2010 - Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization [Details]
- ESANN 2010 - Extending FSNPC to handle data points with fuzzy class assignments [Details]
- ESANN 2010 - Learning vector quantization for heterogeneous structured data [Details]
- ESANN 2010 - Sparse representation of data [Details]
- ESANN 2011 - Generalized functional relevance learning vector quantization [Details]
- ESANN 2011 - Information theory related learning [Details]
- ESANN 2011 - Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization [Details]
- ESANN 2011 - Multispectral image characterization by partial generalized covariance [Details]
- ESANN 2011 - Multivariate class labeling in Robust Soft LVQ [Details]
- ESANN 2011 - Optimization of Parametrized Divergences in Fuzzy c-Means [Details]
- ESANN 2012 - Integration of Structural Expert Knowledge about Classes for Classification Using the Fuzzy Supervised Neural Gas [Details]
- ESANN 2012 - Modified Conn-Index for the evaluation of fuzzy clusterings [Details]
- ESANN 2012 - Recent developments in clustering algorithms [Details]
- ESANN 2012 - Unmixing Hyperspectral Images with Fuzzy Supervised Self-Organizing Maps [Details]
- ESANN 2013 - A sparse kernelized matrix learning vector quantization model for human activity recognition [Details]
- ESANN 2013 - Border sensitive fuzzy vector quantization in semi-supervised learning [Details]
- ESANN 2013 - Non-Euclidean independent component analysis and Oja's learning [Details]
- ESANN 2013 - Processing Hyperspectral Data in Machine Learning [Details]
- ESANN 2013 - Regularization in relevance learning vector quantization using l1-norms [Details]
- ESANN 2014 - Applications of lp-Norms and their Smooth Approximations for Gradient Based Learning Vector Quantization [Details]
- ESANN 2014 - Optimization of General Statistical Accuracy Measures for Classification Based on Learning Vector Quantization [Details]
- ESANN 2014 - Recent trends in learning of structured and non-standard data [Details]
- ESANN 2014 - Supervised Generative Models for Learning Dissimilarity Data [Details]
- ESANN 2014 - Utilization of Chemical Structure Information for Analysis of Spectra Composites [Details]
- ESANN 2015 - Learning matrix quantization and variants of relevance learning [Details]
- ESANN 2015 - Median-LVQ for classification of dissimilarity data based on ROC-optimization [Details]
- ESANN 2016 - Adaptive dissimilarity weighting for prototype-based classification optimizing mixtures of dissimilarities [Details]
- ESANN 2017 - Biomedical data analysis in translational research: integration of expert knowledge and interpretable models [Details]
- ESANN 2018 - Reliable Patient Classification in Case of Uncertain Class Labels Using a Cross-Entropy Approach [Details]
- ESANN 2019 - DropConnect for Evaluation of Classification Stability in Learning Vector Quantization [Details]
- ESANN 2019 - Statistical physics of learning and inference [Details]
- ESANN 2018 - Reliable Patient Classification in Case of Uncertain Class Labels Using a Cross-Entropy Approach [Details]
- ESANN 1993 - Paralell dynamics of extremely diluted neural networks [Details]
- No papers found
- ESANN 2022 - Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine [Details]
- ESANN 2005 - A probabilistic framework for mismatch and profile string kernels [Details]
- ESANN 2012 - Constructive Reservoir Computation with Output Feedbacks for Structured Domains [Details]
- ESANN 2024 - SAT Instances Generation Using Graph Variational Autoencoders [Details]
- ESANN 2005 - Joint Regularization [Details]
- No papers found
- ESANN 2022 - Model Agnostic Local Explanations of Reject [Details]
- ESANN 1994 - Model selection for neural networks: comparing MDL and NIC [Details]
- ESANN 2004 - Reducing connectivity by using cortical modular bands [Details]
- ESANN 2003 - Developmental pruning of synapses and category learning [Details]
- ESANN 2008 - Multilayer perceptron to model the decarburization process in stainless steel production [Details]
- ESANN 2019 - Multi-target feature selection through output space clustering [Details]
- ESANN 2018 - Feature noise tuning for resource efficient Bayesian Network Classifiers [Details]
- ESANN 2002 - Fast nonlinear dimensionality reduction with topology preserving networks [Details]
- ESANN 2003 - Self-Organization by Optimizing Free-Energy [Details]
- ESANN 2014 - Tensor decomposition of dense SIFT descriptors in object recognition [Details]
- ESANN 2000 - Learning principal components in a contextual space [Details]
- ESANN 2020 - Weighted Emprirical Risk Minimization: Transfer Learning based on Importance Sampling [Details]