yusuke1997/dblp-id-title huggingface dataset:
Electric load forecasting using wavelet transform and extreme learning machine
Person Identification and Discovery With Wrist Worn Accelerometer Data
Information retrieval systems using an associative conceptual space
Segmentation of EMG time series using a variational Bayesian approach for the robust estimation of cortical silent periods
Extracting urban water usage habits from smart meter data: a functional clustering approach
Optimizing kernel parameters by second-order methods
A distributed wrapper approach for feature selection
Synchronization and acceleration: complementary mechanisms of temporal coding
Distribution Preserving Multiple Hypotheses Prediction for Uncertainty Modeling
Orthogonality in Additive Echo State Networks
Numerical implementation of continuous Hopfield networks for optimization
Evolutionary algorithms and neural networks in hybrid systems
Spike-timing-dependent plasticity in 'small world' networks
Capturing confounding sources of variation in DNA methylation data by spatiotemporal independent component analysis
Spline-based neuro-fuzzy Kolmogorov's network for time series prediction
Application of high-order Boltzmann machines in OCR
A comparative design of a MIMO neural adaptive rate damping for a nonlinear helicopter model
Enhancement of a stochastic Markov-blanket framework with ant colony optimization, to uncover epistasis in genetic association studies
Approximation capabilities of folding networks
Fourier-based Video Prediction through Relational Object Motion
A Relational Model for One-Shot Classification
Identifying informative features for ERP speller systems based on RSVP paradigm
Enhanced NMF initialization using a physical model for pollution source apportionment
Assessment of sequential Boltmann machines on a lexical processing task
Retinal blood vessel segmentation from high resolution fundus image using deep learning architecture
Empirical evidence of the linear nature of magnetoencephalograms
Once more on the information capacity of the hopefield network
Extending reservoir computing with random static projections: a hybrid between extreme learning and RC
Critical and non-critical avalanche behavior in networks of integrate-and-fire neurons
Laplacian pyramid with multilayer perceptrons interpolators
Semi-supervised bipartite ranking with the normalized Rayleigh coefficient
An overview of reservoir computing: theory, applications and implementations
Efficient reinforcement learning through Evolutionary Acquisition of Neural Topologies
A Variational Approach to Semi-Supervised Clustering
Committee formation for reliable and accurate neural prediction in industry
Classification of handwritten digits using supervised locally linear embedding algorithm and support vector machine
Three dimensional frames of reference transformations using gain modulated populations of neurons
Efficient low rank approximation via alternating least squares for scalable kernel learning
Exploring the role of intrinsic plasticity for the learning of sensory representations
Extreme learning machines for Internet traffic classification
Confidence estimation methods for neural networks : a practical comparison
Binary and Multi-label Defect Classification of Printed Circuit Board based on Transfer Learning
RBClust: High quality class-specific clustering using rule-based classification
Enhanced Deep Reinforcement Learning based Group Recommendation System with Multi-head Attention for Varied Group Sizes
Sequential Continual Pre-Training for Neural Machine Translation
Measuring topology preservation in maps of real-world data
Identification of churn routes in the Brazilian telecommunications market
A stochastic and competitive network for the separation of sources
Kernel PLS variants for regression
Epistemic Risk-Sensitive Reinforcement Learning
Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification
A semi-supervised approach to question classification
A novel interactive biometric passport photograph alignment system
Algorithmic approaches to training Support Vector Machines: a survey
Robust outlier detection with L0-SVDD
High dimensionality voltammetric biosensor data processed with artificial neural networks
Hierarchical Reinforcement Learning for Robot Navigation
Recent methods for dimensionality reduction: A brief comparative analysis
Fisherman learning algorithm of the SOM realized in the CMOS technology
Do we need hundreds of classifiers or a good feature selection?
High frequency forecasting with associative memories
Unsupervised models for processing visual data
Privacy-Preserving Kernel Computation For Vertically Partitioned Data
Range-based non-orthogonal ICA using cross-entropy method
Bayesian periodogram smoothing for speech enhancement
Policy-Based Reinforcement Learning in the Generalized Rock-Paper-Scissors Game
Impact of Biases in Big Data
Improving iterative repair strategies for scheduling with the SVM
More on stationnary points in Independent Component Analysis
Divergence based Learning Vector Quantization
Stochastic quartet approach for fast multidimensional scaling
Optimal Data Projection for Kernel Spectral Clustering
Deep Graph Convolutional Networks for Wind Speed Prediction
Metric learning with relational data
Modular Representations for Weak Disentanglement
Linear Projection based on Noise Variance Estimation - Application to Spectral Data
Efficient Forward Regression with Marginal Likelihood
Improved generalization ability of neurocontrollers by imposing NLq stability constraints
Pattern analysis in illicit heroin seizures: a novel application of machine learning algorithms
A new decision strategy in multi-objective training of the artificial neural networks
Predicting the profitability of agricultural enterprises in dairy farming
a new wrapper method for feature subset selection
Evaluation of gradient descent learning algorithms with adaptive and local learning rate for recognising hand-written numerals
A novel kernel-based method for local pattern extraction in random process signals
On the definition of complex structured feature spaces
Kernel PCA based clustering for inducing features in text categorization
LS-SVM functional network for time series prediction
Self-organizing maps in manifolds with complex topologies: An application to the planning of closed path for indoor UAV patrols
Towards Randomized Algorithms and Models that We Can Trust: a Theoretical Perspective
Morisita-based feature selection for regression problems
A nuclear-norm based convex formulation for informed source separation
Learning contextual affordances with an associative neural architecture
Informational cost in correlation-based neuronal networks
Single-pass uncertainty estimation with layer ensembling for regression: application to proton therapy dose prediction for head and neck cancer
Clustering from two data sources using a kernel-based approach with weight coupling
d-NARMA neural networks: a connectionist extension of ARARMA models
Rotation-based ensembles of RBF networks
Theoretical properties of functional Multi Layer Perceptrons
Algorithmic challenges in big data analytics
Online speaker diarization with a size-monitored growing neural gas algorithm
Model-Free Functional MRI Analysis Using Topographic Independent Component Analysis
Derivation of nonlinear amplitude equations for the normal modes of a self-organizing system
On Transformer Autoregressive Decoding for Multivariate Time Series Forecasting
Input pruning for neural gas architectures
Parallel hardware implementation of a broad class of spiking neurons using serial arithmetic
Conditional prediction of time series using spiral recurrent neural network
Adaptive scene-dependent filters in online learning environments
Load forecasting dealing with medium voltage network reconfiguration
An upper estimate of the error of approximation of continuous multivariable functions by KBF networks
The permutation test for feature selection by mutual information
EEG Source Imaging Enhances Motor Imagery Classification
An Exploration of Research Directions in Machine Ensemble Theory and Applications
Statistical downscaling with artificial neural networks
How to process uncertainty in machine learning?
Evolutionary tuning of multiple SVM parameters
Effect of context in swipe gesture-based continuous authentication on smartphones
Data topology visualization for the Self-Organizing Map
Support Vector Machine For Functional Data Classification
Online One-class Classification for Intrusion Detection Based on the Mahalanobis Distance
Graph extraction from color images
Cost-free resolution enhancement in Convolutional Neural Networks for medical image segmentation
Approximated Neighbours MinHash Graph Node Kernel
Construction of a memory management system in an on-line learning mechanism
Fast hyperparameter selection for graph kernels via subsampling and multiple kernel learning
Improving Fairness via Intrinsic Plasticity in Echo State Networks
Rectified Gaussian distributions and the formation of local filters from video data
Asynchronous decentralized convex optimization through short-term gradient averaging
Implicitly and explicitly constrained optimization problems for training of recurrent neural networks
Softmax Recurrent Unit: A new type of RNN cell
Feature binding and relaxation labeling with the competitive layer model
Communication-Efficient Ridge Regression in Federated Echo State Networks
On the equivalence between regularized NMF and similarity-augmented graph partitioning
On the use of the wavelet decomposition for time series prediction
Unsupervised classifier for monitoring and diagnostic of time series
SOM competition for complex image scene with variant object positions
Efficient accuracy estimation for instance-based incremental active learning
Motor control and movement optimization learned by combining auto-imitative and genetic algorithms
Feature definition, analysis and selection for lung nodule classification in chest computerized tomography images
Estimation of the Human Concentration using Echo State Networks
Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent
Kernelizing Vector Quantization Algorithms
Phase transitions in Vector Quantization
Neural assembly binding in linguistic representation
The CNN computer - a tutorial
Scalable approximate k-NN Graph construction based on Locality Sensitive Hashing
Research directions in interpretable machine learning models
Interactive Machine Learning-Powered Dashboard for Energy Analytics in Residential Buildings
Improved and Generalized Vine Line Detection on Aerial Images Using Asymmetrical Neural Networks and ML Subclassifiers
An agile machine learning project in pharma - developing a Mask R-CNN-based web application for bacterial colony counting
Maximum likelihood learning of RBMs with Gaussian visible units on the Stiefel manifold
Unsupervised learning of motion patterns
Auto-encoder pre-training of segmented-memory recurrent neural networks
2nd European Symposium on Artificial Neural Networks, ESANN 1994, Brussels, Belgium, April 20-22, 1994, Proceedings
Relevance learning in generative topographic maps
Regularization path for Ranking SVM
Increased robustness and intermittent dynamics in structured Reservoir Networks with feedback
Detection of elementary particles with the WiSARD n-tuple classifier
A Real-time PCB Defect Detector Based on Supervised and Semi-supervised Learning
Efficient learning of email similarities for customer support
Adaptive velocity tuning for visual motion estimation
Competitive neural networks for robust computation of the optical flow
Federated Learning in a Semi-Supervised Environment for Earth Observation Data
Median Variant of Fuzzy c-Means
Extraction of crisp logical rules using constrained backpropagation networks
Partially-supervised learning in Independent Factor Analysis
Probabilistic decision trees ans multilayered perceptrons
L1-based compression of random forest models
SOM for intensity inhomogeneity correction in MRI
Decoding stimulation intensity from evoked ECoG activity using support vector regression
Neural field description of state-dependent receptive field changes in the visual cortex
Computational models of intracytoplasmic sperm injection prognosis
Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting
The 'K' in K-fold Cross Validation
Multicriteria optimized MLP for imbalanced learning
Multiple Kernel Self-Organizing Maps
Diluted neural networks with binary couplings: a replica symmetry breaking calculation of the storage capacity
Defending against poisoning attacks in online learning settings
Dynamic pattern selection for faster learning and controlled generalization of neural networks
Efficient voting prediction for pairwise multilabel classification
Analysis of imputation bias for feature selection with missing data
A novel autoassociative memory on the complex hypercubic lattice
Searching the Web: learning based techniques
Learning the appropriate representation paradigm by circular processing units
Yield curve forecasting by error correction neural networks and partial learning
Adversarials-1 in Speech Recognition: Detection and Defence
Joint SVM for Accurate and Fast Image Tagging
Ensemble Learning with Dynamic Ordered Pruning for Regression
CNNGen: A Generator and a Dataset for Energy-Aware Neural Architecture Search
Supervised learning and associative memory by the random neural network
Direct calculation of out-of-sample predictions in multi-class kernel FDA
Efficient estimation of multidimensional regression model with multilayer perceptron
Vision Language Models as Policy Learners in Reinforcement Learning Environments
Storage capacity of the reversed wedge perceptron with binary connections
Context-specific sampling method for contextual explanations
Constraining of weights using regularities
Fast orienting movements to visual targets: neural field model of dynamic gaze control
Transfer learning in Bayesian optimization for the calibration of a beam line in proton therapy
Kernel Temporal Component Analysis
Learning super-resolution 3D segmentation of plant root MRI images from few examples
An algorithm for training multilayer networks on non-numerical data
Hidden Markov gating for prediction of change points in switching dynamical systems
Modelling human sound localization with deep neural networks
Explaining t-SNE Embeddings Locally by Adapting LIME
Multiclass brain computer interface based on visual attention
Classifying mental states with machine learning algorithms using alpha activity decline
Iterative context compilation for visual object recognition
21st European Symposium on Artificial Neural Networks, ESANN 2013, Bruges, Belgium, April 24-26, 2013
Random Forests Model Selection
Hyperparameter Learning in Robust Soft LVQ
A Parameterless t-SNE for Faithful Cluster Embeddings from Prototype-based Learning and CONN Similarity
Simplifying Deep Reservoir Architectures
Estimation of performance bounds in supervised classification
Survival SVM: a practical scalable algorithm
Read classification for next generation sequencing
Deep Reservoir Computing: A Critical Analysis
Diffusion Maps parameters selection based on neighbourhood preservation
Saliency extraction with a distributed spiking neural network
Memory Efficient Weightless Neural Network using Bloom Filter
Probabilistic Adaptation for Meta-Learning
Easy multiple kernel learning
Instance-Based Multi-Label Classification via Multi-Target Distance Regression
Selecting among candidate basis functions by crosscorrelations
Machine learning in distributed, federated and non-stationary environments - recent trends
Fast and reliable architecture selection for convolutional neural networks
Tutorial - Continual Learning beyond classification
Convergence properties of a fuzzy ARTMAP network
An intuitive characterization for the reference vectors of a Kohonen map
Differential private relevance learning
Estimating uncertainty in radiation oncology dose prediction with dropout and bootstrap in U-Net models
Motion Segmentation using Frequency Domain Transformer Networks
Adaptive robot learning in a non-stationary environment
The problem of adaptive control in a living system or how to acquire an inverse model without the help of an external teacher
Self-organized dynamic attractors in recurrent neural networks
Ensembles of genetically trained artificial neural networks for survival analysis
Self Organizing Star (SOS) for health monitoring
Supervised Art-II: a new neural network architecture, with quicker learning algorithm, for learning and classifying multivaled input patterns
On the robust design of uncoupled CNNs
Learning Recurrent Dynamics using Differential Evolution
Optimization of the asymptotic performance of time-domain convolutive source separation algorithms
Combining latent tree modeling with a random forest-based approach, for genetic association studies
Leveraging Physics-Informed Neural Networks as Solar Wind Forecasting Models
Data Mining Techniques on the Evaluation of Wireless Churn
Constructing similarity networks using the Fisher information metric
The role of Fisher information in primary data space for neighbourhood mapping
One Class SVM and Canonical Correlation Analysis increase performance in a c-VEP based Brain-Computer Interface (BCI)
Machine learning for automated quality control in injection moulding manufacturing
The Recurrent Control Neural Network
Self organizing map for adaptive non-stationary clustering: some experimental results on color quantization of image sequences
Using classification to determine the number of finger strokes on a multi-touch tactile device
Combining higher-order N-grams and intelligent sample selection to improve language modeling for Handwritten Text Recognition
Recurrent Feedback Improves Recognition of Partially Occluded Objects
On radial basis function network equalization in the GSM system
Geometric Deep Learning to Enhance Imbalanced Domain Adaptation in EEG
Exploiting hierarchical prediction structures for mixed 2d-3d tracking
Spatial summation in simple cells: computational and experimental results
A Robust Minimal Learning Machine based on the M-Estimator
Training convolutional networks with weight-wise adaptive learning rates
Clarity: a Deep Ensemble for Visual Counterfactual Explanations
Contrasting Explanation of Concept Drift
Time series prediction using DirRec strategy
Minimum entropy queries for linear students learning nonlinear rules
Neural fitted actor-critic
Specification, estimation and evaluation of single hidden-layer feedforward autoregressive artificial neural network models
SOM-based Classification and a Novel Stopping Criterion for Astroparticle Applications
Regularization and neural computation: application to aerial images analysis
Parallel neural hardware: the time is right
A HMM-based pre-training approach for sequential data
Temporal Ensembling-based Deep k-Nearest Neighbours for Learning with Noisy Labels
Multi-perspective embedding for non-metric time series classification
Anomaly Detection Approach in Cyber Security for User and Entity Behavior Analytics System
Biologically plausible hybrid network design and motor control
Sparse least squares Support Vector Machine classifiers
Invited paper: Pruning methods: a review
Multispectral Pedestrian Detection using Deep Fusion Convolutional Neural Networks
On different ensembles of kernel machines
Dynamic functional-link neural networks genetically evolved applied to system identification
Controlling complexity of RBF networks by similarity
Three algorithms for searching the minimum distance in the self-organizing maps
Lattice ICA for the separation of speech signals
FedHP: Federated Learning with Hyperspherical Prototypical Regularization
Analog Brownian weight movement for learning of artificial neural networks
Choosing the Metric in High-Dimensional Spaces Based on Hub Analysis
Adaptive Gabor Filters for Interpretable Color Texture Classification
Machine learning techniques to assess the performance of a gait analysis system
A statistical model selection strategy applied to neural networks
Supervised learning of convex piecewise linear approximations of optimization problems
SVM and pattern-enriched common fate graphs for the game of go
Maximal Discrepancy for Support Vector Machines
Convolutional Transformer via Graph Embeddings for Few-shot Toxicity and Side Effect Prediction
To stop learning using the evidence
Interpretation and comparison of multivariate data partitions
Multivariate class labeling in Robust Soft LVQ
ELM vs. WiSARD: a performance comparison
Monotonic Recurrent Bounded Derivative Neural Network
Near-optimal facial emotion classification using a WiSARD-based weightless system
Analysis of a Reinforcement Learning algorithm using Self-Organizing Maps
Evolutionary RL for Container Loading
Graph Neural Networks for the Prediction of Protein-Protein Interfaces
Self-Organizing Kernel-based Convolutional Echo State Network for Human Actions Recognition
Non-Negative Tensor Dictionary Learning
Recognition of handwritten digits using sparse codes generated by local feature extraction methods
Reinforcement learning in a nutshell
Estimating the intrinsic dimensionality of hyperspectral images
Recognition of consonant-vowel utterances using Support Vector Machines
Scholar Performance Prediction using Boosted Regression Trees Techniques
Almost sure convergence of the one-dimensional Kohonen algorithm
Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness
A self-organizing map for analysis of high-dimensional feature spaces with clusters of highly differing feature density
Order in Complex Systems of Nonlinear Oscillators: Phase Locked Subspaces
Efficient Learning in Spiking Models
Discriminative dimensionality reduction in kernel space
Learning Data Representations with Sparse Coding Neural Gas
Canonical correlation analysis in early vision processing
Sleep analysis in a CLIS patient using soft-clustering: a case study
Patch-based bilateral filter and local m-smoother for image denoising
On the equivalence between algorithms for Non-negative Matrix Factorization and Latent Dirichlet Allocation
Bidirectional deep-readout echo state networks
Integrating the evidence framework and the support vector machine
Hierarchical, prototype-based clustering of multiple time series with missing values
Simplified neural architectures for symmetric boolean functions
Structural Risk Minimization and Rademacher Complexity for Regression
Unsupervised Dimensionality Reduction for Transfer Learning
Linearization identification and an application to BSS using a SOM
An Optimized Learning Algorithm Based on Linear Filters Suitable for Hardware implemented Self-Organizing Maps
An evolutionary approach for optimizing weightless neural networks
An episodic knowledge base for object understanding
Scene classification by an artificial neural network
Distributive Thermometer: A New Unary Encoding for Weightless Neural Networks
ESNigma: efficient feature selection for echo state networks
Comparison of Numerical Models and Statistical Learning for Wind Speed Prediction
Deep Recurrent Graph Neural Networks
Designing nearest neighbour classifiers by the evolution of a population of prototypes
"Mental Images" driven classification
Weightless Neural Networks for text classification using tf-idf
Computational Intelligence in biomedicine: Some contributions
Automatic alignment of medical vs. general terminologies
Towards incremental deep learning: multi-level change detection in a hierarchical visual recognition architecture
A sparse kernelized matrix learning vector quantization model for human activity recognition
Detecting adversarial examples with inductive Venn-ABERS predictors
Classification by means of Evolutionary Response Surfaces
Segmental duration control by time delay neural networks with asymmetric causal and retro-causal information flows
Privacy Preserving Synthetic Health Data
Self-organizing maps based on differential equations
Positive and Scale Invariant Gaussian Process Latent Variable Model for Astronomical Spectra
Visual-based posture recognition using hybrid neural networks
Robust Feature Selection and Robust Training to Cope with Hyperspectral Sensor Shifts