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Adaptive and Learning Systems : Theory and Applications / edited by Kumpati S. Narendra
Adaptive and Learning Systems : Theory and Applications / edited by Kumpati S. Narendra
Pubbl/distr/stampa New York, : Springer, 1986
Descrizione fisica viii, 418 p. : ill. ; 24 cm
Soggetto topico 93-XX - Systems theory; control [MSC 2020]
Soggetto non controllato Adaptive Systems
Adaptive control
Average
Control
Convergence
Fields
Forms
Information
Learning
Models
Systems Theory
Themes
Volume
forum
learning systems
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNICAMPANIA-VAN0268843
New York, : Springer, 1986
Materiale a stampa
Lo trovi qui: Univ. Vanvitelli
Opac: Controlla la disponibilità qui
Adaptive and Learning Systems : Theory and Applications / edited by Kumpati S. Narendra
Adaptive and Learning Systems : Theory and Applications / edited by Kumpati S. Narendra
Pubbl/distr/stampa New York, : Springer, 1986
Descrizione fisica viii, 418 p. : ill. ; 24 cm
Soggetto topico 93-XX - Systems theory; control [MSC 2020]
Soggetto non controllato Adaptive Systems
Adaptive control
Average
Control
Convergence
Fields
Forms
Information
Learning
Models
Systems Theory
Themes
Volume
forum
learning systems
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNICAMPANIA-VAN00268843
New York, : Springer, 1986
Materiale a stampa
Lo trovi qui: Univ. Vanvitelli
Opac: Controlla la disponibilità qui
Advances in Intelligent Data Analysis XVIII [[electronic resource] ] : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings / / edited by Michael R. Berthold, Ad Feelders, Georg Krempl
Advances in Intelligent Data Analysis XVIII [[electronic resource] ] : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings / / edited by Michael R. Berthold, Ad Feelders, Georg Krempl
Autore Berthold Michael
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham, : Springer Nature, 2020
Descrizione fisica 1 online resource (XIV, 588 p. 210 illus., 132 illus. in color.)
Disciplina 005.74
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Database management
Data mining
Computers
Machine learning
Computer organization
Database Management
Data Mining and Knowledge Discovery
Computing Milieux
Machine Learning
Computer Systems Organization and Communication Networks
Soggetto non controllato Database Management
Data Mining and Knowledge Discovery
Computing Milieux
Machine Learning
Computer Systems Organization and Communication Networks
open access
data mining
learning systems
classification
clustering
semantics
learning algorithms
supervised learning
association rules
social networks
graphic methods
neural networks
artificial intelligence
computer vision
correlation analysis
databases
education
engineering
graph theory
image analysis
Databases
Database programming
Data mining
Expert systems / knowledge-based systems
Information technology: general issues
Machine learning
Computer networking & communications
ISBN 3-030-44584-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder -- Dual Sequential Variational Autoencoders for Fraud Detection -- A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks -- Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams -- GraphMDL: Graph Pattern Selection Based on Minimum Description Length -- Towards Content Sensitivity Analysis -- Gibbs Sampling Subjectively Interesting Tiles -- Even Faster Exact k-Means Clustering -- Ising-Based Consensus Clustering on Special Purpose Hardware -- Transfer Learning by Learning Projections from Target to Source -- Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs -- Towards Evaluation of CNN Performance in Semantically Meaningful Latent Spaces -- Vouw: Geometric Pattern Mining Using the MDL Principle -- A Consensus Approach to Improve NMF Document Clustering -- Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams -- Widening for MDL-Based Retail Signature Discovery -- Addressing the Resolution Limit and the Field of View Limit in Community Mining -- Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics -- Adversarial Attacks Hidden in Plain Sight -- Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code -- Overlapping Hierarchical Clustering (OHC) -- Digital Footprints of International Migration on Twitter -- Percolation-Based Detection of Anomalous Subgraphs in Complex Networks -- A Late-Fusion Approach to Community Detection in Attributed Networks -- Reconciling Predictions in the Regression Setting: an Application to Bus Travel Time Prediction -- A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization -- Actionable Subgroup Discovery and Urban Farm Optimization -- AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model -- Detection of Derivative Discontinuities in Observational Data -- Improving Prediction with Causal Probabilistic Variables -- DO-U-Net for Segmentation and Counting -- Enhanced Word Embeddings for Anorexia Nervosa Detection on Social Media -- Event Recognition Based on Classification of Generated Image Captions -- Human-to-AI Coach: Improving Human Inputs to AI Systems -- Aleatoric and Epistemic Uncertainty with Random Forests -- Master your Metrics with Calibration -- Supervised Phrase-Boundary Embeddings -- Predicting Remaining Useful Life with Similarity-Based Priors -- Orometric Methods in Bounded Metric Data -- Interpretable Neuron Structuring with Graph Spectral Regularization -- Comparing the Preservation of Network Properties by Graph Embeddings -- Making Learners (More) Monotone -- Combining Machine Learning and Simulation to a Hybrid Modelling Approach -- LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification -- Angle-Based Crowding Degree Estimation for Many-Objective Optimization.
Record Nr. UNISA-996418219903316
Berthold Michael  
Cham, : Springer Nature, 2020
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in Intelligent Data Analysis XVIII : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings / / edited by Michael R. Berthold, Ad Feelders, Georg Krempl
Advances in Intelligent Data Analysis XVIII : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings / / edited by Michael R. Berthold, Ad Feelders, Georg Krempl
Autore Berthold Michael
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham, : Springer Nature, 2020
Descrizione fisica 1 online resource (XIV, 588 p. 210 illus., 132 illus. in color.)
Disciplina 005.74
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Database management
Data mining
Computers
Machine learning
Computer organization
Database Management
Data Mining and Knowledge Discovery
Computing Milieux
Machine Learning
Computer Systems Organization and Communication Networks
Soggetto non controllato Database Management
Data Mining and Knowledge Discovery
Computing Milieux
Machine Learning
Computer Systems Organization and Communication Networks
open access
data mining
learning systems
classification
clustering
semantics
learning algorithms
supervised learning
association rules
social networks
graphic methods
neural networks
artificial intelligence
computer vision
correlation analysis
databases
education
engineering
graph theory
image analysis
Databases
Database programming
Data mining
Expert systems / knowledge-based systems
Information technology: general issues
Machine learning
Computer networking & communications
ISBN 3-030-44584-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder -- Dual Sequential Variational Autoencoders for Fraud Detection -- A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks -- Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams -- GraphMDL: Graph Pattern Selection Based on Minimum Description Length -- Towards Content Sensitivity Analysis -- Gibbs Sampling Subjectively Interesting Tiles -- Even Faster Exact k-Means Clustering -- Ising-Based Consensus Clustering on Special Purpose Hardware -- Transfer Learning by Learning Projections from Target to Source -- Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs -- Towards Evaluation of CNN Performance in Semantically Meaningful Latent Spaces -- Vouw: Geometric Pattern Mining Using the MDL Principle -- A Consensus Approach to Improve NMF Document Clustering -- Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams -- Widening for MDL-Based Retail Signature Discovery -- Addressing the Resolution Limit and the Field of View Limit in Community Mining -- Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics -- Adversarial Attacks Hidden in Plain Sight -- Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code -- Overlapping Hierarchical Clustering (OHC) -- Digital Footprints of International Migration on Twitter -- Percolation-Based Detection of Anomalous Subgraphs in Complex Networks -- A Late-Fusion Approach to Community Detection in Attributed Networks -- Reconciling Predictions in the Regression Setting: an Application to Bus Travel Time Prediction -- A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization -- Actionable Subgroup Discovery and Urban Farm Optimization -- AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model -- Detection of Derivative Discontinuities in Observational Data -- Improving Prediction with Causal Probabilistic Variables -- DO-U-Net for Segmentation and Counting -- Enhanced Word Embeddings for Anorexia Nervosa Detection on Social Media -- Event Recognition Based on Classification of Generated Image Captions -- Human-to-AI Coach: Improving Human Inputs to AI Systems -- Aleatoric and Epistemic Uncertainty with Random Forests -- Master your Metrics with Calibration -- Supervised Phrase-Boundary Embeddings -- Predicting Remaining Useful Life with Similarity-Based Priors -- Orometric Methods in Bounded Metric Data -- Interpretable Neuron Structuring with Graph Spectral Regularization -- Comparing the Preservation of Network Properties by Graph Embeddings -- Making Learners (More) Monotone -- Combining Machine Learning and Simulation to a Hybrid Modelling Approach -- LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification -- Angle-Based Crowding Degree Estimation for Many-Objective Optimization.
Record Nr. UNINA-9910404119303321
Berthold Michael  
Cham, : Springer Nature, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Entropy Measures for Data Analysis: Theory, Algorithms and Applications
Entropy Measures for Data Analysis: Theory, Algorithms and Applications
Autore Keller Karsten
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (260 p.)
Soggetto non controllato fault diagnosis
empirical mode decomposition
auditory attention
Dempster-Shafer evidence theory
simulation
uncertainty of basic probability assignment
center of pressure displacement
particle size distribution
multivariate analysis
symbolic analysis
permutation entropy
short time records
co-evolution
plausibility transformation
experiment of design
cross-entropy method
weighted Hartley entropy
firefly algorithm
embedded dimension
entropy measure
effective transfer entropy
treadmill walking
ordinal patterns
complex fuzzy set
entropy visualization
belief entropy
signal classification
machine learning evaluation
novelty detection
selfsimilar measure
Permutation entropy
automatic learning
cross wavelet transform
cross-visibility graphs
Kolmogorov-Sinai entropy
distance
Shannon-type relations
Tsallis entropy
market crash
support vector machine (SVM)
conditional entropy of ordinal patterns
sample entropy
learning
electroencephalography (EEG)
meta-heuristic
entropy
data transformation
information entropy
signal analysis
synchronization analysis
similarity indices
data analysis
geodesic distance
auditory attention classifier
entropy measures
distance induced vague entropy
analog circuit
vague entropy
complex vague soft set
entropy balance equation
parametric t-distributed stochastic neighbor embedding
global optimization
learning systems
image entropy
algorithmic complexity
support vector machine
system coupling
relevance analysis
Chinese stock sectors
Shannon entropy
linear discriminant analysis (LDA)
information
information transfer
dual-tasking
non-probabilistic entropy
ISBN 3-03928-033-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Entropy Measures for Data Analysis
Record Nr. UNINA-9910367736303321
Keller Karsten  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Nonparametric Statistical Inference with an Emphasis on Information-Theoretic Methods
Nonparametric Statistical Inference with an Emphasis on Information-Theoretic Methods
Autore Mielniczuk Jan
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (226 p.)
Soggetto topico Technology: general issues
History of engineering & technology
Mechanical engineering & materials
Soggetto non controllato high-dimensional time series
nonstationarity
network estimation
change points
kernel estimation
high-dimensional regression
loss function
random predictors
misspecification
consistent selection
subgaussianity
generalized information criterion
robustness
statistical learning theory
information theory
entropy
parameter estimation
learning systems
privacy
prediction methods
misclassification risk
model misspecification
penalized estimation
supervised classification
variable selection consistency
archimedean copula
consistency
estimation
extreme-value copula
tail dependency
multivariate analysis
conditional mutual information
CMI
information measures
nonparametric variable selection criteria
gaussian mixture
conditional infomax feature extraction
CIFE
joint mutual information criterion
JMI
generative tree model
Markov blanket
minimum distance estimation
maximum likelihood estimation
influence functions
adaptive splines
B-splines
right-censored data
semiparametric regression
synthetic data transformation
time series
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910576873203321
Mielniczuk Jan  
MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui