yusuke1997/dblp-id-title huggingface dataset:
Memory Transfer in DRASiW-like Systems
On the dynamics of Vector Quantization and Neural Gas
Asymptotic statistics for multilayer perceptron with ReLu hidden units
A State-Space Model for the Dynamic Random Subgraph Model
Grouping complex face parts by nonlinear oscillations
Revisiting the Mark Conditional Independence Assumption in Neural Marked Temporal Point Processes
Face recognition: pre-processing techniques for linear autoassociators
Graph based neural networks for automatic classification of multiple sclerosis clinical courses
Variants of Neural Gas for Regression Learning
Random Signal Cut for Improving Multimodal CNN Robustness of 2D Road Object Detection
An efficient learning model for the neural integrator of the oculomotor system
Evolving multi-segment 'super-lamprey' CPG's for increased swimming control
Deep hybrid approach for 3D plane segmentation
A time-scale correlation-based blind separation method applicable to correlated sources
The Benefits of Adversarial Defence in Generalisation
An augmented efficient backpropagation training strategy for deep autoassociative neural networks
Design of Power-Efficient FPGA Convolutional Cores with Approximate Log Multiplier
Comparison of traditional and neural systems for train speed estimation
Cross-modal verification for 3D object detection
Learning for stochastic dynamic programming
Unsupervised Real-time Anomaly Detection for Multivariate Mobile Phone Traffic Series
Toward a robust 2D spatio-temporal self-organization
Highly efficient localisation utilising weightless neural systems
BIOSEG: a bioinspired vlsi analog system for image segmentation
Analyzing spatial dissimilarities in high-resolution geo-data : a case study of four European cities
An EM transfer learning algorithm with applications in bionic hand prostheses
Large Language Models as Tuning Agents of Metaheuristics
What are the main factors involved in the design of a Radial Basis Function Network?
The architecture of emergent self-organizing maps to reduce projection errors
Learning Visual Invariance
Lukasiewicz fuzzy logic networks and their ultra low power hardware implementation
Independence is far from normal
An Alternating Minimization Algorithm with Trajectory for Direct Exoplanet Detection
interpretation of convolutional neural networks for speech regression from electrocorticography
Nonlinear source separation: the post-nonlinear mixtures
Revisiting Edge Pooling in Graph Neural Networks
Speedy greedy feature selection: Better redshift estimation via massive parallelism
Biochemical Pathway Robustness Prediction with Graph Neural Networks
Real-time Detection of Evoked Potentials by Deep Learning: a Case Study
Localized discriminative Gaussian process latent variable model for text-dependent speaker verification
RSS-based Robot Localization in Critical Environments using Reservoir Computing
Distance functions for local PCA methods
On the analysis of feature selection techniques in a conjunctival hyperemia grading framework
Brain-like intelligent control: from neural nets to larger-scale systems
Neuro-wavelet parametric characterization of hardness profiles
clustering using a random walk based distance measure
Connection strategies in neocortical networks
Computational model for amygdala neural networks
LEAP nets for power grid perturbations
Stacked denoising autoencoders for the automatic recognition of microglial cells' state
FPGA implementation of an integrate-and-fire LEGION model for image segmentation
Very Simple Classifier: a concept binary classifier to investigate features based on subsampling and locality
Adaptive dissimilarity weighting for prototype-based classification optimizing mixtures of dissimilarities
CRE: Circle relationship embedding of patches in vision transformer
Frequency Domain Transformer Networks for Video Prediction
Marble slabs quality classification system using texture recognition and neural networks methodology
Suboptimal Bayesian classification by vector quantization with small clusters
A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences
Anticipating Rewards in Continuous Time and Space with Echo State Networks and Actor-Critic Design
A hierarchical model for syllable recognition
From Three to Two Dimensions: 2D Quaternion Convolutions for 3D Images
Lightweight Cross-Modal Representation Learning
Automatic Singular Spectrum Analysis for Time-Series Decomposition
Noise reduction by multi-target learning
A critique of BCM behavior verification for STDP-type plasticity models
Similarities and differences between policy gradient methods and evolution strategies
Intelligent hardware for identification and control of non-linear systems with SVM
On the Speedup of Deep Reinforcement Learning Deep Q-Networks (RL-DQNs)
TimeNet: Pre-trained deep recurrent neural network for time series classification
Graph projection techniques for Self-Organizing Maps
Using degree constrained gravity null-models to understand the structure of journeys' networks in bicycle sharing systems
Synthetic over-sampling in the empirical feature space
An Empirical Study of Iterative Knowledge Distillation for Neural Network Compression
Reproducing kernels and regularization methods in machine learning
SMO Lattices for the Parallel Training of Support Vector Machines
Risk Estimation and Feature Selection
A novel two-layer neural network classifier
Approximation of Function by Adaptively Growing Radial Basis Function Neural Networks
Detecting zebra crossings utilizing AdaBoost
lightweight autonomous bayesian optimization of Echo-State Networks
Cluster detection algorithm in neural networks
Joint Regularization
Improvement in Game Agent Control Using State-Action Value Scaling
The prediction of learning performance using features of note taking activities
Input arrival-time-dependent decoding scheme for a spiking neural network
Reliability of dimension reduction visualizations of hierarchical structures
Support Vector Ordinal Regression using Privileged Information
Noise derived information criterion for model selection
Time series forecasting using CCA and Kohonen maps - application to electricity consumption
32nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2024, Bruges, Belgium, October 9-11, 2024
Integration of Structural Expert Knowledge about Classes for Classification Using the Fuzzy Supervised Neural Gas
Connectionist solutions for energy management systems
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
A Fast and Simple Evolution Strategy with Covariance Matrix Estimation
Extended Bayesian learning
Complex activity patterns generated by short-term synaptic plasticity
Improving Light-weight Convolutional Neural Networks for Face Recognition Targeting Resource Constrained Platforms
Neural networks for fault diagnosis and identification of industrial processes
Interpretable ensembles of local models for safety-related applications
Bounds on the degree of high order binary perceptrons
Spiral Recurrent Neural Network for Online Learning
Learning predictive partitions for continuous feature spaces
Fisher memory of linear Wigner echo state networks
Neural networks for computational neuroscience
Constraints as Alternative Learning Objective in Deep Learning
Curves clustering with approximation of the density of functional random variables
Multispectral image characterization by partial generalized covariance
Slope: A First-order Approach for Measuring Gradient Obfuscation
An asymmetric associative memory model based on relaxation labeling processes
30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2022, Bruges, Belgium, October 5-7, 2022
An Experiment in Pre-Emphasizing Diversified Deep Neural Classifiers
A probabilistic framework for mismatch and profile string kernels
Federated Learning approach for SpectralClustering
Neural networks for modelling memory : case studies
Swim velocity profile identification through a Dynamic Self-adaptive Multiobjective Harmonic Search and RBF neural networks
Recent trends in learning of structured and non-standard data
Learning Object-Class Segmentation with Convolutional Neural Networks
Spectral Prototype Extraction for dimensionality reduction in brain tumour diagnosis
29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2021, Online event (Bruges, Belgium), October 6-8, 2021
Sparse one hidden layer MLPs
Toward STDP-based population action in large networks of spiking neurons
Subject Categorization for Web Educational Resources using MLP
Noise robustness in the perceptron
Toward parallel feature selection from vertically partitioned data
A supervised strategy for deep kernel machine
An accelerated MDM algorithm for SVM training
An algorithm for fast and reliable ESOM learning
Neurocontrol of a binary distillation column
Translation invariant classification of non-stationary signals
Capabilities of a structured neural network. Learning and comparison with classical techniques
Quantifying Resemblance of Synthetic Medical Time-Series
Exploring Self-Organizing Maps for Addressing Semantic Impairments
Statistical physics of learning and inference
A Kernel Based Multilinear SVD Approach for Multiple Sclerosis Profiles Classification
Combining neural networks and optimization techniques for visuokinesthetic prediction and motor planning
An objective function for self-limiting neural plasticity rules
Generalization by structural properties from sparse nested symbolic data
Support vector algorithms as regularization networks
ELM Preference Learning for Physiological Data
Improved Cat Swarm Optimization approach applied to reliability-redundancy problem
Human detection and classification of landing sites for search and rescue drones
A Deep Q-Learning Agent for L-Game with Variable Batch Training
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
How regular is neuronal activity?
Hidden Markov models for time series of counts with excess zeros
K-spectral centroid: extension and optimizations
Deconvolution in nonparametric statistics
Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning
Neural Net with Two Hidden Layers for Non-Linear Blind Source Separation
Data mining techniques for feature selection in blood cell recognition
An adjustable p-exponential clustering algorithm
A Neural Graph Isomorphism Algorithm based on local Invariants
The challenges in spectral image analysis: an introduction, and review of ANN approaches
Comparison of optimized backpropagation algorithms
Emergence of stimulus-specific synchronous response through STDP in recurrent neural networks
Dynamic Graph Echo State Networks
Detection and quantification in real-time polymerase chain reaction
Fast and good initialization of RBF networks
Modeling face recognition learning in early infant development
Matrix relevance LVQ in steroid metabolomics based classification of adrenal tumors
Unsupervised dimensionality reduction: the challenge of big data visualization
Connectionist models investigating representations formed in the sequential generation of characters
Computerized tool for identification and enhanced visualization of Macular Edema regions using OCT scans
Designing neural network committees by combining boosting ensembles
Novelty detection in image recognition using IRF Neural Networks properties
Opposite neighborhood: a new method to select reference points of minimal learning machines
Mixtures of robust probabilistic principal component analyzers
Adaptive Optimization for Cross Validation
Description of the Group Dynamic of Funds' Managers using Kohonen's Map
A sequence-encoding neural network for face recognition
Transductively Learning from Positive Examples Only
Robust object segmentation by adaptive metrics in Generalized LVQ
Unsupervised domain adaptation of deep object detectors
Probabilistic derivation and Multiple Canonical Correlation Analysis
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?
Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine
High-accuracy value-function approximation with neural networks applied to the acrobot
Metric learning with submodular functions
Online Bayesian Shrinkage Regression
Perplexity-free Parametric t-SNE
Attention-based Ingredient Phrase Parser
Replacing eligibility trace for action-value learning with function approximation
Detection of two Gaussian clusters
Supervised variable clustering for classification of NIR spectra
HMM and IOHMM modeling of EEG rhythms for asynchronous BCI systems
DYNG: Dynamic Online Growing Neural Gas for stream data classification
Depth and height aware semantic RGB-D perception with convolutional neural networks
Multilayer Perceptrons with Radial Basis Functions as Value Functions in Reinforcement Learning
Neural network based one-step ahead control and its stability
FouriER: Link Prediction by Mixing Tokens with Fourier-enhanced MetaFormer
An Algorithmic Approach to Establish a Lower Bound for the Size of Semiring Neural Networks
Dimensionality reduction in a hydraulic valve positioning application
Application of Dynamic Time Warping on Kalman Filtering Framework for Abnormal ECG Filtering
Image reconstruction using an iterative SOM based algorithm
Detection of abnormal driving situations using distributed representations and unsupervised learning
VisCoDeR: A tool for visually comparing dimensionality reduction algorithms
Augmented hashing for semi-supervised scenarios
Efficient prediction of x-axis intercepts of discrete impedance spectra
An optimized RBF network for approximation of functions
Combining back-propagation and genetic algorithms to train neural networks for start-up time modeling in combined cycle power plants
Self-Organizing Maps computing on Graphic Process Unit
Learning in a chaotic neural network
A generalised label noise model for classification
Improvement on Generative Adversarial Network for Targeted Drug Design
A sliding mode controller using neural networks for robot manipulator
Learning Rich Event Representations and Interactions for Temporal Relation Classification
MLP modular networks for multi-class recognition
Augmenting Information from Brain-Computer Interfaces through Bayesian Plan Recognition
Mixture states in Potts neural networks
A comparison of three PCA neural techniques
Interactive visual analytics for medical data: application to COVID-19 clinical information during the first wave
Detecting Black-box Adversarial Examples through Nonlinear Dimensionality Reduction
On the invertibility of the RBF model in a predictive control strategy
Parallelization of Deep Networks
Fuzzy entropy-constrained competitive learning algorithm
Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river
Knowledge Distillation for Anomaly Detection
A new learning algorithm for incremental self-organizing maps
Fast approximation of the bootstrap for model selection
Embedding-based next song recommendation for playlists
Shallow and Deep Models for Domain Adaptation problems
Freeform surface induction from projected planar curves via neural networks
An Efficient Neural Architecture Search Model for Medical Image Classification
Speaker normalization with a mixture of recurrent networks
On Finding Complementary Clusterings
3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution
Relevance learning for mental disease classification
Simplified cascade-correlation learning
The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals
Probabilistic Classification Vector Machine at large scale
Fuzzy LP-SVMs for Multiclass Problems
Neural network hardware architecture for pattern recognition in the HESS2 project
Benefits and limits of the self-organizing map and its variants in the area of satellite remote sensoring processing
Emerging trends in machine learning: beyond conventional methods and data
Meaningful discretization of continuous features for association rules mining by means of a SOM
Synchronization and oscillations in the visual cortex: a stochastic model using a spike memory term
Robust Bayes Point Machines
Residual Reservoir Computing Neural Networks for Time-series Classification
Reservoir regularization stabilizes learning of Echo State Networks with output feedback
Artificial Neural Networks on Massively Parallel Computer Hardware
Radar Based Pedestrian Detection using Support Vector Machine and the Micro Doppler Effect
Federated Learning - Methods, Applications and beyond
Optimal decision surfaces in LVQ1 classiffication of patterns
Temporal transfer learning for drift adaptation
Dimension reduction for individual ica to decompose FMRI during real-world experiences: principal component analysis vs. canonical correlation analysis
Imitation learning for a continuum trunk robot
Weightless neural systems for deforestation surveillance and image-based navigation of UAVs in the Amazon forest
Deep learning of visual control policies
Automatic selection of the number of spatial filters for motor-imagery BCI
Learning how to grasp objects
Conditional BRUNO: a neural process for exchangeable labelled data
Supporting GNG-based clustering with local input space histograms
SDE U-Net: Disentangling Aleatoric and Epistemic Uncertainties in Medical Image Segmentation
Probabilistic automata simulation with single layer weightless neural networks
A faster model selection criterion for OP-ELM and OP-KNN: Hannan-Quinn criterion
Combined scattering for rotation invariant texture analysis
Evaluating SOMs using order metrics
A hidden Markov model with Hawkes process-derived contextual variables to improve time series prediction. Case study in medical simulation
I.C.A.: conditions on cumulants and information theoretic approach
Feature Selection for Multi-label Classification with Minimal Learning Machine
Neural networks for invariant pattern recognition
Neural methods for non-standard data
Application of MLP and stochastic simulations for electricity load forecasting in Russia
Finding correlations in multimodal data using decomposition approaches
Voronoï tesselation, space quantization algorithms and numerical integration
Anomaly detection in star light curves using hierarchical Gaussian processes
Invariant measure for an infinite neural network
Independent dynamics subspace analysis
Fusing Features based on Signal Properties and TimeNet for Time Series Classification
Bootstrap feature selection in support vector machines for ventricular fibrillation detection
An algorithm to learn sequences within the connectionist sequential machine
Using Wikipedia with associative networks for document classification
A pseudoregression formulation of emphasized soft target procedures for classification problems
Prediction of dynamical systems with composition networks
Time Series Prediction using Disentangled Latent Factors
stellar formation rates in galaxies using machine learning models
A new penalisation term for image retrieval in clique neural networks
Incremental category learning in a real world artifact using growing dynamic cell structures
Predicting spike-timing of a thalamic neuron using a stochastic synaptic model
Regulated Activation Weights Neural Network (RAWN)
Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives
On the long-term learning ability of LSTM LMs
Generalised Cross Validation for Noise-Free Data
Why will rat's go where rats will not?
Parallelized unsupervised feature selection for large-scale network traffic analysis
Analysis of Synaptic Weight Distribution in an Izhikevich Network
predicting bed demand in a hospital using neural networks and ARIMA models: a hybrid approach
Visual focus with spiking neurons
Prediction of mental development of preterm newborns at birth time using LS-SVM
Is Boredom an Indicator on the way to Singularity of Artificial Intelligence? Hypotheses as Thought-Provoking Impulse
Multi-Step Ahead Forecasting of Road Condition Using Least Squares Support Vector Regression
Neural versus neurofuzzy systems for credit approval
DEKF-LSTM
Domain Knowledge Integration in Machine Learning Systems - An Introduction
Continuous convolutional object tracking
Embedding of FRPN in CNN architecture
interpretable dynamics models for data-efficient reinforcement learning
The K.U.Leuven competition data: a challenge for advanced neural network techniques
Comparison of sparse least squares support vector regressors trained in primal and dual
Semi-Supervised Neural Gas for Adaptive Brain-Computer Interfaces
Exploratory Data Analysis in Medicine and Bioinformatics
Time series and neural: a statistical method for weight elimination
Financial predictions based on bootstrap-neural networks
Appearance-Context aware Axial Attention for Fashion Landmark Detection
Use of artificial neural networks process analyzers: a case study
Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control
Median-LVQ for classification of dissimilarity data based on ROC-optimization
Fairness and Accountability of Machine Learning Models in Railway Market: are Applicable Railway Laws Up to Regulate Them?
Temporal modeling of ALS using longitudinal data and long-short term memory-based algorithm
Neurosymbolic integration: unified versus hybrid approaches
Recent trends in online learning for cognitive robots
Entropy-based principle and generalized contingency tables
Mutual information based feature selection for mixed data
An introduction to learning in web domains
Type 1 and 2 symmetric divergences for stochastic neighbor embedding
A new model selection approach for the ELM network using metaheuristic optimization
A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases
A reservoir activation kernel for trees
Supervised and unsupervised classification approaches for human activity recognition using body-mounted sensors
Exploring High- and Low-Density Electroencephalography for a Dream Decoding Brain-Computer Interface
Adapting Random Forests to Cope with Heavily Censored Datasets in Survival Analysis
A self-training method for learning to rank with unlabeled data
HDBSCAN for 3-rd order tensor
Lightening CNN architectures by regularization driven weights' pruning
CMOS design of focal plane programmable array processors
Machine learning in cancer research: implications for personalised medicine
Clustering data streams with weightless neural networks
Constraint optimization for Echo State Networks applied to satellite image forecasting
Toward encryption with neural network analogy
Orthogonal transformations for optimal time series prediction
A Bayesian approach to combined neural networks forecasting
Real-time activity recognition via deep learning of motion features
Robust and Cheap Safety Measure for Exoskeletal Learning Control with Estimated Uniform PAC (EUPAC)
High-dimensional labeled data analysis with Gabriel graphs
Automatic detection of EEG arousals
Optimization by Variational Bounding
Zero phase-lag synchronization through short-term modulations
Domain expert approximation through oracle learning
Single-trial P300 detection with Kalman filtering and SVMs
Forecasting using twinned principal curves
Direct Model-Predictive Control
A-LSSVM: an Adaline based iterative sparse LS-SVM classifier
Spiking AGREL
Specialization with cortical models: An application to causality learning
Behavior Constraining in Weight Space for Offline Reinforcement Learning
Time delay neural network for target-intercept problem solving
Active set training of support vector regressors
Pattern Recognition using Chaotic Transients
A performance acceleration algorithm of spectral unmixing via subset selection
Interpreting Hybrid AI through Autodecoded Latent Space Entities
Applying Mutual Information for Prototype or Instance Selection in Regression Problems
Parallel asynchronous distributed computations of optimal control in large state space Markov Decision processes
Towards Better Transition Modeling in Recurrent Neural Networks: the Case of Sign Language Tokenization
On the Potential Inadequacy of Mutual Information for Feature Selection