yusuke1997/dblp-id-title huggingface dataset:
Training integrate-and-fire neurons with the Informax principle II
Direct Parallel Perceptrons (DPPs): Fast Analytical Calculation of the Parallel Perceptrons Weights With Margin Control for Classification Tasks
Locality Preservation for Unsupervised Multimodal Change Detection in Remote Sensing Imagery
DQC-ADMM: Decentralized Dynamic ADMM With Quantized and Censored Communications
New Parameter-Free Simplified Swarm Optimization for Artificial Neural Network Training and its Application in the Prediction of Time Series
Stability analysis of Cohen-Grossberg neural networks
DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip
Brain-Inspired Meta-Learning for Few-Shot Bearing Fault Diagnosis
General Hyperspectral Image Super-Resolution via Meta-Transfer Learning
Learning the global maximum with parameterized learning automata
Scale-Aware Super-Resolution Network With Dual Affinity Learning for Lesion Segmentation From Medical Images
Spectral-Spatial Global Graph Reasoning for Hyperspectral Image Classification
Partition-Based Solutions of Static Logical Networks With Applications
RadDQN: A Deep Q Learning-Based Architecture for Finding Time-Efficient Minimum Radiation Exposure Pathway
Spiking Neural Network for Ultralow-Latency and High-Accurate Object Detection
On multiple training for bidirectional associative memory
A Survey on Text-Guided 3-D Visual Grounding: Elements, Recent Advances, and Future Directions
Hopfield Neural Networks With Delays Driven by Colored Noise
Efficient Quantum Image Classification Using Single Qubit Encoding
SOIM: a self-organizing invertible map with applications in active vision
On the Kalman filtering method in neural network training and pruning
Simultaneous State and Unknown Input Estimation for Complex Networks With Redundant Channels Under Dynamic Event-Triggered Mechanisms
Fast ML Estimation for the Mixture of Factor Analyzers via an ECM Algorithm
Scalable Kernel Ordinal Regression via Doubly Stochastic Gradients
Training a Dynamic Growing Mixture Model for Lifelong Learning
Theoretical limitations of a Hopfield network for crossbar switching
Exponential Stability of Discrete-Time Genetic Regulatory Networks With Delays
Deep Clustering: A Comprehensive Survey
STSF: Spiking Time Sparse Feedback Learning for Spiking Neural Networks
Prototype-Incorporated Emotional Neural Network
A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain
Synchronization Control of Neural Networks With State-Dependent Coefficient Matrices
New Discrete-Time Recurrent Neural Network Proposal for Quadratic Optimization With General Linear Constraints
A Graph-Embedding Approach to Hierarchical Visual Word Mergence
Memory-Efficient Class-Incremental Learning for Image Classification
Combination of Manifold Learning and Deep Learning Algorithms for Mid-Term Electrical Load Forecasting
Automatic Searching and Pruning of Deep Neural Networks for Medical Imaging Diagnostic
Robust Stability Criterion for Discrete-Time Uncertain Markovian Jumping Neural Networks With Defective Statistics of Modes Transitions
Adaptive NN-Based Event-Triggered Containment Control for Unknown Nonlinear Networked Systems
Joint State and Unknown Input Estimation for a Class of Artificial Neural Networks With Sensor Resolution: An Encoding-Decoding Mechanism
TransXNet: Learning Both Global and Local Dynamics With a Dual Dynamic Token Mixer for Visual Recognition
Graph Theory-Based Approach for Stability Analysis of Stochastic Coupled Systems With Lévy Noise on Networks
Global Convergence of Online BP Training With Dynamic Learning Rate
A CMOS feedforward neural-network chip with on-chip parallel learning for oscillation cancellation
NACHOS: Neural Architecture Search for Hardware-Constrained Early-Exit Neural Networks
DVSRNet: Deep Video Super-Resolution Based on Progressive Deformable Alignment and Temporal-Sparse Enhancement
Reduced Support Vector Machines: A Statistical Theory
Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation
Multitrend Conditional Value at Risk for Portfolio Optimization
Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming
Interpretable Design of Reservoir Computing Networks Using Realization Theory
A Convex Model for Support Vector Distance Metric Learning
A spatially constrained mixture model for image segmentation
A Neural Network Model to Minimize the Connected Dominating Set for Self-Configuration of Wireless Sensor Networks
Bisection Neural Network Toward Reconfigurable Hardware Implementation
Dynamic Affinity Graph Construction for Spectral Clustering Using Multiple Features
Face Sketch Synthesis by Multidomain Adversarial Learning
A Deep Supervised Learning Framework for Data-Driven Soft Sensor Modeling of Industrial Processes
Stability of Delayed Reaction-Diffusion Neural-Network Models With Hybrid Impulses via Vector Lyapunov Function
Comments on "Fractional Extreme Value Adaptive Training Method: Fractional Steepest Descent Approach"
Revisiting Initializing Then Refining: An Incomplete and Missing Graph Imputation Network
Deeply Supervised Block-Wise Neural Architecture Search
Import Vector Domain Description: A Kernel Logistic One-Class Learning Algorithm
Aggregation Analysis for Competitive Multiagent Systems With Saddle Points via Switching Strategies
Integration of Encoding and Temporal Forecasting: Toward End-to-End NO x Prediction for Industrial Chemical Process
Effects of normalization constraints on competitive learning
Learning Discriminative Representation for Co-Salient Object Detection
Reverse Graph Learning for Graph Neural Network
The Margitron: A Generalized Perceptron With Margin
Training neural networks with additive noise in the desired signal
Controllability of N-Duplication Corona Product Networks With Laplacian Dynamics
Identifying Community-Bridge Network Structures via Bayesian Learning With Mixed Sparsity Mode
An algorithmic approach to adaptive state filtering using recurrent neural networks
Event-Triggered Neural-Network Adaptive Control for Strict-Feedback Nonlinear Systems: Selections on Valid Compact Sets
DualConv: Dual Convolutional Kernels for Lightweight Deep Neural Networks
Convolution Filter Compression via Sparse Linear Combinations of Quantized Basis
Learning to Assess Image Quality Like an Observer
TPDC: Point Cloud Completion by Triangular Pyramid Features and Divide-and-Conquer in Complex Environments
Unsupervised Abundance Matrix Reconstruction Transformer-Guided Fractional Attention Mechanism for Hyperspectral Anomaly Detection
Probabilistic Classification Vector Machines
Cognitive navigation based on nonuniform Gabor space sampling, unsupervised growing networks, and reinforcement learning
A Generalized Hopfield Network for Nonsmooth Constrained Convex Optimization: Lie Derivative Approach
Multilevel Contrastive Multiview Clustering With Dual Self-Supervised Learning
Cyclical Curriculum Learning
Subgraph Propagation and Contrastive Calibration for Incomplete Multiview Data Clustering
Model-Based Clustering by Probabilistic Self-Organizing Maps
Tensor Completion Using Bilayer Multimode Low-Rank Prior and Total Variation
Two conditions for equivalence of 0-norm solution and 1-norm solution in sparse representation
A Cascaded Multimodule Image Enhancement Framework for Underwater Visual Perception
Polarity Loss: Improving Visual-Semantic Alignment for Zero-Shot Detection
Learning With Interpretable Structure From Gated RNN
Toward Optimal Synthesis of Discrete-Time Hopfield Neural Network
Deep Fusion Clustering Network With Reliable Structure Preservation
Entropy-Based Incremental Variational Bayes Learning of Gaussian Mixtures
Self-Attention Fully Convolutional DenseNets for Automatic Salt Segmentation
Finite-Horizon H ∞ Tracking Control for Unknown Nonlinear Systems With Saturating Actuators
Model complexity control for regression using VC generalization bounds
Self-Organizing Neural Networks Integrating Domain Knowledge and Reinforcement Learning
Metalearning-Based Alternating Minimization Algorithm for Nonconvex Optimization
TopicBERT: A Topic-Enhanced Neural Language Model Fine-Tuned for Sentiment Classification
Partially connected feedforward neural networks structured by input types
Robust Few-Shot Learning for User-Provided Data
On the Optimal Class Representation in Linear Discriminant Analysis
Complete and partial fault tolerance of feedforward neural nets
Taking on the curse of dimensionality in joint distributions using neural networks
Global Convergence of Decomposition Learning Methods for Support Vector Machines
Neural Network Based Online Simultaneous Policy Update Algorithm for Solving the HJI Equation in Nonlinear H ∞ Control
Automatic change detection of driving environments in a vision-based driver assistance system
INGC-GAN: An Implicit Neural-Guided Cycle Generative Approach for Perceptual-Friendly Underwater Image Enhancement
Neural net robot controller with guaranteed tracking performance
Pulse-coupled neural networks for contour and motion matchings
Incremental learning methods with retrieving of interfered patterns
Matrix Variate Distribution-Induced Sparse Representation for Robust Image Classification
Closing the Gap Between Theory and Practice During Alternating Optimization for GANs
A Three-Stage Optimal Operation Strategy of Interconnected Microgrids With Rule-Based Deep Deterministic Policy Gradient Algorithm
Localizing From Classification: Self-Directed Weakly Supervised Object Localization for Remote Sensing Images
Fully Convolutional Network-Based Self-Supervised Learning for Semantic Segmentation
Unsupervised learning in noise
Adaptive structures with algebraic loops
Further Results on Adaptive Stabilization of High-Order Stochastic Nonlinear Systems Subject to Uncertainties
Neighbor-Based Completion for Addressing Incomplete Multiview Clustering
Policy Iteration Approach to the Infinite Horizon Average Optimal Control of Probabilistic Boolean Networks
Modeling Activity-Dependent Plasticity in BCM Spiking Neural Networks With Application to Human Behavior Recognition
Global Reinforcement Learning in Neural Networks
A Ranking-Based Cross-Entropy Loss for Early Classification of Time Series
A low-complexity fuzzy activation function for artificial neural networks
Concurrent Learning-Based Adaptive Control of Underactuated Robotic Systems With Guaranteed Transient Performance for Both Actuated and Unactuated Motions
Mining Maximal Dynamic Spatial Colocation Patterns
Deep Probabilistic Principal Component Analysis for Process Monitoring
Noise-Tuning-Based Hysteretic Noisy Chaotic Neural Network for Broadcast Scheduling Problem in Wireless Multihop Networks
A Real-Time Framework for EEG Signal Decoding With Graph Neural Networks and Reinforcement Learning
A Gradient-Aware Search Algorithm for Constrained Markov Decision Processes
Flow to Candidate: Temporal Knowledge Graph Reasoning With Candidate-Oriented Relational Graph
Soft learning vector quantization and clustering algorithms based on non-Euclidean norms: multinorm algorithms
Using wavelet network in nonparametric estimation
Temporal and spatial stability in translation invariant linear resistive networks
Boosting Generalization of Semantic Segmentation With Unseen Style Seeking-Based Meta-Learning
A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning
Global Exponential Stability of Impulsive Fuzzy High-Order BAM Neural Networks With Continuously Distributed Delays
A Multitask Learning Model for Online Pattern Recognition
A neural network regulator for turbogenerators
Genetics-based machine learning for the assessment of certain neuromuscular disorders
Theme-Aware Aesthetic Distribution Prediction With Full-Resolution Photographs
Integrated Sliding Mode Control and Neural Networks Based Packet Disordering Prediction for Nonlinear Networked Control Systems
Incremental Unsupervised Domain-Adversarial Training of Neural Networks
Learning Spike Time Codes Through Morphological Learning With Binary Synapses
Multiresolution Interpretable Contourlet Graph Network for Image Classification
Execution of a remote sensing application on a custom neurocomputer
The evolving tree-analysis and applications
Deep Learning for Dynamic Graphs: Models and Benchmarks
Robust Switching Time Optimization for Networked Switched Systems via Model Predictive Control
Partial Multiview Representation Learning With Cross-View Generation
On the design of dynamic associative neural memories
Open Set Domain Adaptation With Soft Unknown-Class Rejection
Multitask Learning for Classification Problem via New Tight Relaxation of Rank Minimization
Multistability of State-Dependent Switched Fractional-Order Hopfield Neural Networks With Mexican-Hat Activation Function and Its Application in Associative Memories
A complex valued radial basis function network for equalization of fast time varying channels
Advances on BYY harmony learning: information theoretic perspective, generalized projection geometry, and independent factor autodetermination
Fuzzy Neural Network Control of a Flexible Robotic Manipulator Using Assumed Mode Method
Event-Triggered Cardinality-Constrained Cooling and Electrical Load Dispatch Based on Collaborative Neurodynamic Optimization
Image Set Classification Using a Distance-Based Kernel Over Affine Grassmann Manifold
Some efficient strategies for improving the eigenstructure method in synthesis of feedback neural networks
STRIP - a strip-based neural-network growth algorithm for learning multiple-valued functions
Incremental Concept Learning via Online Generative Memory Recall
Solving the quadratic assignment problem with clues from nature
Complete Delay-Decomposing Approach to Asymptotic Stability for Neural Networks With Time-Varying Delays
Variants of self-organizing maps
Universal Approximation by Using the Correntropy Objective Function
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp With Metalearning
The multilayer perceptron as an approximation to a Bayes optimal discriminant function
Multimodel Feature Reinforcement Framework Using Moore-Penrose Inverse for Big Data Analysis
Learning mixture models with the regularized latent maximum entropy principle
Deterministic convergence of an online gradient method for BP neural networks
Seeds: Sampling-Enhanced Embeddings
Hamiltonian-Driven Adaptive Dynamic Programming With Efficient Experience Replay
Binary Higher Order Neural Networks for Realizing Boolean Functions
Hierarchical One-Class Classifier With Within-Class Scatter-Based Autoencoders
Principal component extraction using recursive least squares learning
A New Local Bipolar Autoassociative Memory Based on External Inputs of Discrete Recurrent Neural Networks With Time Delay
Information Recovery-Driven Deep Incomplete Multiview Clustering Network
On-line training of recurrent neural networks with continuous topology adaptation
Neural-network approximation of piecewise continuous functions: application to friction compensation
Learning a Tracking and Estimation Integrated Graphical Model for Human Pose Tracking
Errata to "Model Transitions in Descending FLVQ"
Event-Triggered Cluster Consensus of Multi-Agent Systems via a Modified Genetic Algorithm
Sparse Approximation to the Eigensubspace for Discrimination
Neural-Network-Based Finite-Time Bipartite Containment Control for Fractional-Order Multi-Agent Systems
On neural networks that design neural associative memories
A New Concept of Multiple Neural Networks Structure Using Convex Combination
Dynamical analysis of the brain-state-in-a-box (BSB) neural models
Finite-/Fixed-Time Stability of Nonautonomous Functional Differential Inclusion: Lyapunov Approach Involving Indefinite Derivative
MBA: Mini-Batch AUC Optimization
ORCCA: Optimal Randomized Canonical Correlation Analysis
Evolving space-filling curves to distribute radial basis functions over an input space
A Sequential Learning Approach for Scaling Up Filter-Based Feature Subset Selection
k-NS: A Classifier by the Distance to the Nearest Subspace
Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems
Emergent synchrony in locally coupled neural oscillators
A Stochastic Sampling Mechanism for Time-Varying Formation of Multiagent Systems With Multiple Leaders and Communication Delays
Low-Complexity Approximate Convolutional Neural Networks
New Delay-Dependent Stability Criteria for Neural Networks With Time-Varying Delay
Probabilistic Safety Regions via Finite Families of Adjustable Classifiers
Generalized haar DWT and transformations between decision trees and neural networks
Voiced-speech representation by an analog silicon model of the auditory periphery
ChebMixer: Efficient Graph Representation Learning With MLP Mixer
Minimum-Volume-Constrained Nonnegative Matrix Factorization: Enhanced Ability of Learning Parts
Stochastic Finite-Time H ∞ State Estimation for Discrete-Time Semi-Markovian Jump Neural Networks With Time-Varying Delays
Central Attention Network for Hyperspectral Imagery Classification
SATF: A Scalable Attentive Transfer Framework for Efficient Multiagent Reinforcement Learning
Multi-Task Credible Pseudo-Label Learning for Semi-Supervised Crowd Counting
Decentralized Dynamic Event-Triggered Output Feedback Adaptive Fixed-Time Funnel Control for Interconnection Nonlinear systems
Using unsupervised analysis to constrain generalization bounds for support vector classifiers
Guided Policy Exploration for Markov Decision Processes Using an Uncertainty-Based Value-of-Information Criterion
Probabilistic PCA Self-Organizing Maps
Efficient Probabilistic Classification Vector Machine With Incremental Basis Function Selection
Matching Pursuit Network: An Interpretable Sparse Time-Frequency Representation Method Toward Mechanical Fault Diagnosis
On convergence properties of pocket algorithm
The Boundedness Conditions for Model-Free HDP(λ)
Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data
Long-Term Tracking of Evasive Urban Target Based on Intention Inference and Deep Reinforcement Learning
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Adaptive Weighted Broad Echo State Learning System-Based Dynamic Modeling of Carbon Consumption in Sintering Process
A Hierarchical Framework With Spatio-Temporal Consistency Learning for Emergence Detection in Complex Adaptive Systems
Neural network implementation using a single MOST per synapse
Unsupervised Subspace Learning With Flexible Neighboring
CLEAR: Cluster-Enhanced Contrast for Self-Supervised Graph Representation Learning
Enhancing Unsupervised Anomaly Detection With Score-Guided Network
PRSOM: a new visualization method by hybridizing multidimensional scaling and self-organizing map
Random Online Hashing for Cross-Modal Retrieval
Improving the Timing Resolution of Positron Emission Tomography Detectors Using Boosted Learning - A Residual Physics Approach
Predefined-Time Hierarchical Coordinated Neural Control for Hypersonic Reentry Vehicle
Symmetric Nonnegative Matrix Factorization-Based Community Detection Models and Their Convergence Analysis
Toward Multilabel Classification for Multiple Disease Prediction Using Gut Microbiota Profiles
Neural-network methods for boundary value problems with irregular boundaries
Shared Nearest-Neighbor Quantum Game-Based Attribute Reduction With Hierarchical Coevolutionary Spark and Its Application in Consistent Segmentation of Neonatal Cerebral Cortical Surfaces
Training Recurrent Neurocontrollers for Real-Time Applications
Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting
3-D Brain Reconstruction by Hierarchical Shape-Perception Network From a Single Incomplete Image
Fully Complex-Valued Dendritic Neuron Model
Distributed Extremum Seeking for Optimal Resource Allocation and Its Application to Economic Dispatch in Smart Grids
On the Sufficient Condition for Solving the Gap-Filling Problem Using Deep Convolutional Neural Networks
TECO: A Unified Feature Map Compression Framework Based on Transform and Entropy
Hybrid Rubbing Fault Identification Using a Deep Learning-Based Observation Technique
Data-Based Controllability and Observability Analysis of Linear Discrete-Time Systems
Data-Driven Multiagent Systems Consensus Tracking Using Model Free Adaptive Control
Analog design of a new neural network for optical character recognition
A new one-layer neural network for linear and quadratic programming
IRPruneDeXt: Efficient Infrared Small Target Detection via Musical Wavelet-Regularized Channel Pruning
Statistically controlled activation weight initialization (SCAWI)
Hamiltonian-Driven Adaptive Dynamic Programming for Continuous Nonlinear Dynamical Systems
Edge-Aware Network for Flow-Based Video Frame Interpolation
Probably Approximately Correct Bayes Meta-Learning With Parameterized-Bounded Guarantees
DenseKD: Dense Knowledge Distillation by Exploiting Region and Sample Importance
Multiscale Information Diffusion Prediction With Minimal Substitution Neural Network
Hardware implementation of CMAC neural network with reduced storage requirement
Multigranularity Information Fused Contrastive Learning With Multiview Clustering
Double-Graph Representation With Relational Enhancement for Emotion-Cause Pair Extraction
Reconstruction Regularized Deep Metric Learning for Multi-Label Image Classification
Tradeoff Analysis Between Control Time and Energy Consumption for Delayed Neural Networks With Discontinuous Activation Functions
Exponential Stabilization of Memristor-based Chaotic Neural Networks with Time-Varying Delays via Intermittent Control
Discrete-time convergence theory and updating rules for neural networks with energy functions
Representation of a fisher criterion function in a kernel feature space
Stabilizing Effects of Impulses in Discrete-Time Delayed Neural Networks
Input space versus feature space in kernel-based methods
Memory Models of Adaptive Behavior
Efficient Gradient Support Pursuit With Less Hard Thresholding for Cardinality-Constrained Learning
Markov Boundary-Based Outlier Mining
Temporal difference learning applied to sequential detection
Refining Euclidean Obfuscatory Nodes Helps: A Joint-Space Graph Learning Method for Graph Neural Networks
Multistability and Instability of Neural Networks With Discontinuous Nonmonotonic Piecewise Linear Activation Functions
The truth will come to light: directions and challenges in extracting the knowledge embedded within trained artificial neural networks
A New Criterion of Delay-Dependent Asymptotic Stability for Hopfield Neural Networks With Time Delay
Robust Curve Clustering Based on a Multivariate t -Distribution Model
PID Controller-Guided Attention Neural Network Learning for Fast and Effective Real Photographs Denoising
Convolutive Bounded Component Analysis Algorithms for Independent and Dependent Source Separation
Adaptive Control for Nonlinear Pure-Feedback Systems With High-Order Sliding Mode Observer
Local Sample-Weighted Multiple Kernel Clustering With Consensus Discriminative Graph
Neural-network predictive control for nonlinear dynamic systems with time-delay
Fast Filter Pruning via Coarse-to-Fine Neural Architecture Search and Contrastive Knowledge Transfer
Image compression by self-organized Kohonen map
Gaussian filters and filter synthesis using a Hermite/Laguerre neural network
Adaptive NN Finite-Time Resilient Control for Nonlinear Time-Delay Systems With Unknown False Data Injection and Actuator Faults
Regression methods for pricing complex American-style options
Self-stabilized gradient algorithms for blind source separation with orthogonality constraints
Neural controller for adaptive movements with unforeseen payloads
Beyond Pattern Variance: Unsupervised 3-D Action Representation Learning With Point Cloud Sequence
Regression modeling in back-propagation and projection pursuit learning
Denoiser Learning for Infrared and Visible Image Fusion
H ∞ State Estimation for Discrete-Time Complex Networks With Randomly Occurring Sensor Saturations and Randomly Varying Sensor Delays
Uncertainty Estimation With Neural Processes for Meta-Continual Learning
Heterogeneous fuzzy logic networks: fundamentals and development studies