yusuke1997/dblp-id-title huggingface dataset:
Local model optimization for time series prediction
19th European Symposium on Artificial Neural Networks, ESANN 2011, Bruges, Belgium, April 27-29, 2011, Proceedings
Complex Valued Gated Auto-encoder for Video Frame Prediction
Geometric overcomplete ICA
Anomalous Cluster Detection in Large Networks with Diffusion-Percolation Testing
An Associative Memory for the Automorphism Group of Structures
Beyond Pham's algorithm for joint diagonalization
Evolved Neurodynamics for Robot Control
Methodology and standards for data analysis with machine learning tools
RetinotopicNET: An Efficient Simulator for Retinotopic Visual Architectures
Iterative learning neural network control for nonlinear system trajectory tracking
Magnification control in neural maps
WIPS: the WiSARD Indoor Positioning System
Boundary based movement correction of functional MR data using a genetic algorithm
13th European Symposium on Artificial Neural Networks, ESANN 2005, Bruges, Belgium, April 27-29, 2005, Proceedings
Deep convolutional neural networks for detecting noisy neighbours in cloud infrastructure
Nonlinear transient computation and variable noise tolerance
Classification of Boar Sperm Head Images using Learning Vector Quantization
Learning Inverse Dynamics: a Comparison
Using distributed genetic programming to evolve classifiers for a brain computer interface
Evaluation methodology for disentangled uncertainty quantification on regression models
Adaptive matrix distances aiming at optimum regression subspaces
A Robust Neural Robot Navigation Using a Combination of Deliberative and Reactive Control Architectures
Incremental increased complexity training
Supervised Generative Models for Learning Dissimilarity Data
Collaborative Filtering with interlaced Generalized Linear Models
Knowledge discovery in DNA microarray data of cancer patients with emergent self organizing maps
Bayesian non-parametric parsimonious clustering
Using Deep Learning and Evolutionary Algorithms for Time Series Forecasting
Handling missing values in kernel methods with application to microbiology data
Misclassification of class C G-protein-coupled receptors as a label noise problem
Generalizing Convolution to Point Clouds
Matching analogue hardware with applications using the Products of Experts algorithm
Information theory related learning
Weighted/Structured Total Least Squares problems and polynomial system solving
Biomedical data analysis in translational research: integration of expert knowledge and interpretable models
An explicit comparison of spike dynamics and firing rate dynamics in neural network modeling
Neural networks for the solution of information-distributed optimal control problems
On the number of latent representations in deep neural networks for tabular data
Improving Laplacian Pyramids Regression with Localization in Frequency and Time
Self-organization in mixture densities of HMM based speech recognition
Robustness and Regularization in Hierarchical Re-Basin
PAC-Bayes and Fairness: Risk and Fairness Bounds on Distribution Dependent Fair Priors
Maximal Discrepancy vs. Rademacher Complexity for error estimation
Locally implementable learning with isospectral matrix flows
An alternative approach for the evaluation of the neocognitron
Comprehensive Analysis of the Screening of COVID-19 Approaches in Chest X-ray Images from Portable Devices
Efficient Neural-based patent document segmentation with Term Order Probabilities
Gaussian process prediction for time series of structured data
Entropy Based Regularization Improves Performance in the Forward-Forward Algorithm
Neural dimensionality reduction for document processing
A Random Forest proximity matrix as a new measure for gene annotation
Feature clustering and mutual information for the selection of variables in spectral data
Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting
Neural approaches to independent component analysis and source separation
A neural network approach to adaptive pattern analysis - the deformable feature map
Regularizing generalization error estimators: a novel approach to robust model selection
Information visualisation and machine learning: characteristics, convergence and perspective
Non-negative matrix factorization as a pre-processing tool for travelers temporal profiles clustering
On the complexity of shallow and deep neural network classifiers
Investigating lexical access using neural nets
Joint optimization of predictive performance and selection stability
Heteroscedastic regularised kernel regression for prediction of episodes of poor air quality
Gaussian and exponential architectures in small-world associative memories
Continual Learning at the Edge: Real-Time Training on Smartphone Devices
Physics-Aware Normalizing Flows: Leveraging Electric Circuit Models in Adversarial Learning
Weight saliency regularization in augmented networks
A Spiking Machine for Human-Computer Interactions (Design methodology)
A New Error-Correcting Syndrome Decoder with Retransmit Signal Implemented with an Hardlimit Neural Network
Consistent estimation of the architecture of multilayer perceptrons
Automatic relevance determination for Least Squares Support Vector Machines classifiers
Variants of Unsupervised Kernel Regression: General cost functions
Automatic classification of prostate cancer using pseudo-gaussian radial basis function neural network
Predicting Grain Protein Content of Winter Wheat
Mixture of Hidden Markov Model as Tree Encoder
Segmentation and Analysis of Lumbar Spine MRI Scans for Vertebral Body Measurements
New conditioning model for robots
Face identification using support vector machines
Spatial Chirp-Z Transformer Networks
Connectionist rule processing using recursive auto-associative memory
Improving object recognition by using a visual latency mechanism
Classification of chestnuts with feature selection by noise resilient classifiers
1D vs 2D convolutional neural networks for scalp high frequency oscillations identification
Few-shot similarity learning for motion classification via electromyography
VLSI complexity reduction by piece-wise approximation of the sigmoid function
Brain Computer Interface for Virtual Reality Control
Quantum RAM Based Neural Netoworks
Neural network classification using Shannon's entropy
Neural Maps and Learning Vector Quantization - Theory and Applications
Improving Pedestrian Recognition using Incremental Cross Modality Deep Learning
Functional radial basis function networks
Anomaly detection in irregular image sequences for concentrated solar power plants
Some known facts about financial data
Hierarchical clustering for graph visualization
A Stability Condition for Neural Network Control of Uncertain Systems
Relevance determination in Learning Vector Quantization
Patch Affinity Propagation
Visualizing the trustworthiness of a projection
Trajectory learning using hierarchy of oscillatory modules
Representing hierarchical relationships using a modified Asymmetric SOM Algorithm
Perception and action selection by anticipation of sensorimotor consequences
Initialization of big data clustering using distributionally balanced folding
Experimental validation of a synapse model by adding synaptic conductances to excitable endocrine cells in culture
Improving the Robustness of Bagging with Reduced Sampling Size
Negative initial weights improve learning in recurrent neural networks
Non-Euclidean independent component analysis and Oja's learning
Visual person tracking with a Supervised Conditioning-SOM
Pruned lazy learning models for time series prediction
A robust regularization path for the Doubly Regularized Support Vector Machine
Tumor Grading via Decorrelated Sparse Survival Regression
Hybrid HMM/MLP models for times series prediction
27th European Symposium on Artificial Neural Networks, ESANN 2019, Bruges, Belgium, April 24-26, 2019
Error rate estimation via cross-validation and learning curve theory
Outlier identification with the Harmonic Topographic Mapping
Input data reduction for the prediction of financial time series
Hierarchical markovian models for joint classification, segmentation and data reduction of hyperspectral images
Predicting vehicle behaviour using LSTMs and a vector power representation for spatial positions
gNBXe - a Reconfigurable Neuroprocessor for Various Types of Self-Organizing Maps
Trustworthiness Score for Echo State Networks by Analysis of the Reservoir Dynamics
Spiking neural networks with Hebbian plasticity for unsupervised representation learning
22th European Symposium on Artificial Neural Networks, ESANN 2014, Bruges, Belgium, April 23-25, 2014
Fuzzy Fleiss-kappa for Comparison of Fuzzy Classifiers
Time Series Analysis for Quality Improvement: a Soft Computing Approach
A neural approach to a sensor fusion problem
Simultaneous estimation of rewards and dynamics from noisy expert demonstrations
Robust Visual Terrain Classification with Recurrent Neural Networks
Soft-computing techniques for time series forecasting
Functional Resonant Synaptic Clusters for Decoding Time-Structured Spike Trains
Topologically Ordered Graph Clustering via Deterministic Annealing
Mutual information and gamma test for input selection
Agglomerative hierarchical kernel spectral clustering for large scale networks
Sample efficient localization and stage prediction with autoencoders
Size Scaling in Self-Play Reinforcement Learning
Towards an effective multi-map self organizing recurrent neuronal network
Machine learning for medical applications
Towards cognitive automotive environment modelling: reasoning based on vector representations
Prediction of preterm infant mortality with Gaussian process classification
Hardware Implementation Issues of the Neighborhood Mechanism in Kohonen Self Organized Feature Maps
Multi-target feature selection through output space clustering
A bayesian variational principle for dynamic self organizing maps
Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system
Feature binding in deep convolution networks with recurrences, oscillations, and top-down modulated dynamics
Tree-recursive computation of gradient information for structures
On the error function of interval arithmetic backpropagation
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Learning sparse representations of three-dimensional objects
Hybrid Deep Learning-Based Air and Water Quality Prediction Model
Human feedback in continuous actor-critic reinforcement learning
Weighted differential topographic function: a refinement of topographic function
Sparse mixture of von Mises-Fisher distribution
Visualization of the Feature Space of Neural Networks
Unmixing Hyperspectral Images with Fuzzy Supervised Self-Organizing Maps
Graph-cut-assisted CNN training for pulmonary embolism segmentation
LLaMA Tunes CMA-ES
Experimental study of the neuron-level mechanisms emerging from backpropagation
Projection of undirected and non-positional graphs using Self Organizing Maps
A deterministic method for establishing the initial conditions in the RCE algorithm
Towards a Tomographic Index of Systemic Risk Measures
Missing Image Data Imputation using Variational Autoencoders with Weighted Loss
Topic-based historical information selection for personalized sentiment analysis
Deep Learning Vector Quantization
Discriminative learning for neural decision feedback equalizers
From User-independent to Personal Human Activity Recognition Models Using Smartphone Sensors
AdaBoost and neural networks
Initialization mechanism in Kohonen neural network implemented in CMOS technology
Hybrid modelling of dynamic anaerobic digestion process in full-scale with LSTM NN and BMP measurements
Synthesis of maximum margin and multiview learning using unlabeled data
Design of Oscillatory Recurrent Neural Network Controllers with Gradient based Algorithms
Controlling biological neural networks with deep reinforcement learning
Performance of weighted radial basis function classifiers
Learning VOR-like stabilization reflexes in robots
Recurrent V1-V2 interaction for early visual information processing
Learning from Reward as an emergent property of Physics-like interactions between neurons in an artificial neural network
Improving accuracy by reducing the importance of hubs in nearest-neighbor recommendations
Feasibility based Large Margin Nearest Neighbor metric learning
Inverting hyperspectral images with Gaussian Regularized Sliced Inverse Regression
Anomaly detections on the oil system of a turbofan engine by a neural autoencoder
About the Kohonen algorithm: strong or weak self-organization?
Pruning Neural Networks with Supermasks
Meerkats-inspired Algorithm for Global Optimization Problems
Linear Scalarized Knowledge Gradient in the Multi-Objective Multi-Armed Bandits Problem
Simple reservoirs with chain topology based on a single time-delay nonlinear node
Complexity bounds of radial basis functions and multi-objective learning
Locally Weighted Least Squares Temporal Difference Learning
Generalized matrix learning vector quantizer for the analysis of spectral data
Evidence of efficiency of recurrent neural networks with ARMA-like units
Post-failure analysis of an adaptive predictor-corrector neural controller on a flight simulator
Societal Issues in Machine Learning: When Learning from Data is Not Enough
Deep Echo State Networks for Functional Ambulation Categories Estimation
Support Vector Committee Machines
Deep Neural Networks for Classification of Riding Patterns: with a focus on explainability
Some new results on the coding of pheromone intensity in an olfactory sensory neuron
Multiobjective Reinforcement Learning in Optimized Drug Design
Leveraging performance-based metadata for designing multi-objective NAS strategies for efficient models in Earth Observation
Bayesian non parametric inference of discrete valued networks
Automatic Pain Intensity Recognition: Training Set Selection based on Outliers and Centroids
Contextual Processing of Graphs using Self-Organizing Maps
Projection learning: alternative approaches to the computation of the projection
Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs
Exponential stability of stochastic, retarded neural netorks
Coordinate descent on the Stiefel manifold for deep neural network training
The NeuralBAG algorithm: optimizing generalization performance in bagged neural networks
Selection of more than one gene at a time for cancer prediction from gene expression data
Green Machine Learning
Adaptative time constants improve the dynamic features of recurrent neural networks
Fault diagnosis of an electro-pneumatic valve actuator using neural networks with fuzzy capabilities
Active learning strategy for CNN combining batchwise Dropout and Query-By-Committee
Cache-efficient Gradient Descent Algorithm
Attacking Model Sets with Adversarial Examples
Order Crossover for the Inventory Routing Problem
Evaluation of Contrastive Learning for Electronic Component Detection
Classification of high-dimensional data for cervical cancer detection
15th European Symposium on Artificial Neural Networks, ESANN 2007, Bruges, Belgium, April 25-27, 2007, Proceedings
Mobile radio access network monitoring using the self-organizing map
Neural Architecture Search for Sentence Classification with BERT
Regularization in relevance learning vector quantization using l1-norms
A neural model of cross-modal association in insects
Latent representations of transient candidates from an astronomical image difference pipeline using Variational Autoencoders
Tensor Decompositions in Recursive Neural Networks for Tree-Structured Data
Functional topographic mapping for robust handling of outliers in brain tumour data
Manifold-based non-parametric learning of action-value functions
A heterogeneous database for movement knowledge extraction in Parkinson's disease
9th European Symposium on Artificial Neural Networks, ESANN 2001, Bruges, Belgium, April 25-27, 2001, Proceedings
Convolutional Neural Network Architecture for Classification of Aircraft Engines Flight Time Series
XAI and Bias of Deep Graph Networks
Efficient approximate representations for computationally expensive features
Rosen's projection method for SVM training
A fast Bayesian algorithm for Boolean functions synthesis by means of perceptron networks
Navigational Freespace Detection for Autonomous Driving in Fixed Routes
Training a sigmoidal network is difficult
Clustering a medieval social network by SOM using a kernel based distance measure
Algebraic inversion of an artificial neural network classifier
Improving piecewise linear separation incremental algorithms using complexity reduction methods
A fast learning algorithm for high dimensional problems: an application to microarrays
A computational model of monkey grating cells for oriented repetitive alternating patterns
Causality analysis of LFPs in micro-electrode arrays based on mutual information
Neuromimetic motion indicator for visual perception
Secure Federated Learning with Kernel Affine Hull Machines
Recurrent SOM with local linear models in time series prediction
Large-Scale Continuous Structure Learning from Time-Series Data
A post-processing strategy for SVM learning from unbalanced data
Learning search-control heuristics for automated deduction systems with folding architecture networks
Detection and Localization of GAN Manipulated Multi-spectral Satellite Images
Modal sense classification with task-specific context embeddings
Word Embeddings for Morphologically Rich Languages
Continual Incremental Language Learning for Neural Machine Translation
Frontiers in Reservoir Computing
About Vector Quantization and its Privacy in Federated Learning
Neuromimetic model of interval timing
Capturing variabilities from Computed Tomography images with Generative Adversarial Networks (GANs)
The combination of STDP and intrinsic plasticity yields complex dynamics in recurrent spiking networks
Fine-grained event learning of human-object interaction with LSTM-CRF
Incremental evolution of neural network architectures for adaptive behavior
Image registration by the extended evolutionary self-organizing map
Handling almost-deterministic relationships in constraint-based Bayesian network discovery : Application to cancer risk factor identification
Unsupervised Recursive Sequence Processing
Boosting by weighting boundary and erroneous samples
Classifying Patterns in a Spiking Neural Network
Hierarchical Combination of Video Features for Personalised Pain Level Recognition
A decision support system based on cellular automata to help the control of late blight in tomato cultures
Wind power forecasting based on bagging extreme learning machine ensemble model
Dual Stream Graph Transformer Fusion Networks for Enhanced Brain Decoding
Weight perturbation learning algorithm with local learning rate adaptation for the classification of remote-sensing images
Temperature Forecast in Buildings Using Machine Learning Techniques
Stochastic resonance and finite resolutions in a leaky integrate-and-fire neuron
Hybrid vibration signal monitoring approach for rolling element bearings
Nonlinear factorization in sparsely encoded Hopfield-like neural networks
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization
Do We Really Need a New Theory to Understand the Double-Descent?
Learning multimodal fixed-point weights using gradient descent
Classification and Prediction in Highly Dimensional Spaces - An Application to Tribology
A neural network model of landmark recognition in the fiddler crab, Uca lactea
Regularize and explicit collaborative filtering with textual attention
Seq-to-NSeq model for multi-summary generation
Interpretability of machine learning models and representations: an introduction
A Novel Two-Phase SOM Clustering Approach to Discover Visitor Interests in a Website
Using graph-theoretic measures to predict the performance of associative memory models
Learning with monotonicity requirements for optimal routing with end-to-end quality of service constraints
A new approach based on wavelet-ICA algorithms for fetal electrocardiogram extraction
Beta Distribution Drift Detection for Adaptive Classifiers
Sensitivity to parameter and data variations in dimensionality reduction techniques
Rates of approximation of real-valued boolean functions by neural networks
Accelerating the convergence speed of neural networks learning methods using least squares
Free-swinging and locked joint fault detection and isolation in cooperative manipulators
Classifying Scotch Whisky from near-infrared Raman spectra with a Radial Basis Function Network with Relevance Learning
Improving neural network estimation in presence of non i.i.d. noise
Non-orthogonal Support Width ICA
A Counterexample to Ockham's Razor and the Curse of Dimensionality: Marginalising Complexity and Dimensionality for GMMs
Clustering in data space and feature space
Aeronautic data analysis
Self-Supervised Learning from Incrementally Drifting Data Streams
Multivariate Time Series Multi-Coclustering. Application to Advanced Driving Assistance System Validation
Order between logic networks and stable neural networks
Investigating 3D-STDenseNet for Explainable Spatial Temporal Crime Forecasting
Sparsity Issues in Self-Organizing-Maps for Structures
Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks
The purkinje unit of the cerebellum as a model of a stable neural network
Supervised learning as preference optimization
Averaging on Riemannian manifolds and unsupervised learning using neural associative memory
Online multiclass learning with "bandit" feedback under a Passive-Aggressive approach
Weighted tree kernels for sequence analysis
Trust, law and ideology in a NN agent model of the US Appellate Courts
6th European Symposium on Artificial Neural Networks, ESANN 1998, Bruges, Belgium, April 22-24, 1998, Proceedings
Minimerror: a perceptron learning rule that finds the optimal weights
FairBayRank: A Fair Personalized Bayesian Ranker
Cellular topographic self-organization under correlational learning
TrIK-SVM : an alternative decomposition for kernel methods in Kreı̆n spaces
Generalization properties of spiking neurons trained with ReSuMe method
GA-KDE-Bayes: an evolutionary wrapper method based on non-parametric density estimation applied to bioinformatics problems
Lag selection for regression models using high-dimensional mutual information
Hidden Markov Models for Temporal Graph Representation Learning
The Nonlinear Dynamic State neuron
Autoencoding time series for visualisation
Feature and Algorithm Selection for Capacitated Vehicle Routing Problems
Echo State networks and Neural network Ensembles to predict Sunspots activity
Rank-constrained optimization: a Riemannian manifold approach
Recent advances in efficient learning of recurrent networks
Neural networks organizations to learn complex robotic functions
Revisiting ant colony algorithms to seismic faults detection
Deep Weisfeiler-Lehman assignment kernels via multiple kernel learning
support vector machine-based aproach for multi-labelers problems
How to project 'circular' manifolds using geodesic distances?
Using Shannon Entropy as EEG Signal Feature for Fast Person Identification
A self-organising neural network for modelling cortical development
Feature Relevance Bounds for Linear Classification
Dynamical reservoir properties as network effects
Unveiling Dreams: Moving Towards Automatic Dream Decoding via PSD-Based EEG Analysis and Machine Learning
SOM algorithms and their stability consideration
Knowledge Discovery in Quarterly Financial Data of Stocks Based on the Prime Standard using a Hybrid of a Swarm with SOM
Deep multi-task learning with evolving weights
ManiSonS: A New Visualization Tool for Manifold Clustering
CAS-Net: A Novel Coronary Artery Segmentation Neural Network
Machine Learning for Measuring and Analyzing Online Social Communications
Fast online adaptivity with policy gradient: example of the BCI "P300"-speller
A Tropical View of Graph Neural Networks
Nonlinearity and separation capability: further justification for the ICA algorithm with mixture of densities
A hierarchical self-organizing feature map for analysis of not well separable clusters of different feature density