Toward optimally distributed computation
Neural Computation
Issues in Bayesian analysis of neural network models
Neural Computation
Computation with infinite neural networks
Neural Computation
Bayesian radial basis functions of variable dimension
Neural Computation
Robust Sensor Fusion: Analysis and Application to Audio Visual Speech Recognition
Machine Learning - Special issue on context sensitivity and concept drift
Bayesian Function Learning Using MCMC Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Classification With Gaussian Processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparison of approximate methods for handling hyperparameters
Neural Computation
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multistrategy Approach to Classifier Learning from Time Series
Machine Learning - Special issue on multistrategy learning
The generalized Bayesian committee machine
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Upper and Lower Bounds on the Learning Curve for Gaussian Processes
Machine Learning
Minimum-Entropy Data Partitioning Using Reversible Jump Markov Chain Monte Carlo
IEEE Transactions on Pattern Analysis and Machine Intelligence
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application
Data Mining and Knowledge Discovery
Dynamic Learning with the EM Algorithm for Neural Networks
Journal of VLSI Signal Processing Systems
Adaptive Metric Kernel Regression
Journal of VLSI Signal Processing Systems
Neural Network Modelling with Input Uncertainty: Theory and Application
Journal of VLSI Signal Processing Systems
Interpolation models with multiple hyperparameters
Statistics and Computing
Statistics and Computing
Structural Modelling with Sparse Kernels
Machine Learning
Machine Learning
Metalearning and neuromodulation
Neural Networks - Computational models of neuromodulation
An approach to guaranteeing generalisation in neural networks
Neural Networks
Combining Belief Networks and Neural Networks for Scene Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Will Domain-Specific Code Synthesis Become a Silver Bullet?
IEEE Intelligent Systems
Approximate algorithms for neural-Bayesian approaches
Theoretical Computer Science - Natural computing
MLP in layer-wise form with applications to weight decay
Neural Computation
Joint classifier and feature optimization for cancer diagnosis using gene expression data
RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
Bayesian Learning Techniques: Application to Neural Networks with Constraints on Weight Space
WIRN VIETRI 2002 Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers
The Bias-Variance Dilemma of the Monte Carlo Method
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Missing Value Estimation Using Mixture of PCAs
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
High Precision Measurement of Fuel Density Profiles in Nuclear Fusion Plasmas
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Neural Learning Invariant to Network Size Changes
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Mining Dependence Structures from Statistical Learning Perspective
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
The Hierarchical Neuro-Fuzzy BSP Model: An Application in Electric Load Forecasting
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Bayesian Neural Network Learning for Prediction in the Australian Dairy Industry
IDA '99 Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis
Forward and Backward Selection in Regression Hybrid Network
MCS '02 Proceedings of the Third International Workshop on Multiple Classifier Systems
AIME '01 Proceedings of the 8th Conference on AI in Medicine in Europe: Artificial Intelligence Medicine
Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Feature Extraction and Selection in Tool Condition Monitoring System
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
RBF neural networks for classification using new kernel functions
Second international workshop on Intelligent systems design and application
Generalized relevance learning vector quantization
Neural Networks - New developments in self-organizing maps
On different facets of regularization theory
Neural Computation
Data mining tasks and methods: Classification: neural network approaches
Handbook of data mining and knowledge discovery
Mining biomolecular data using background knowledge and artificial neural networks
Handbook of massive data sets
Clustering ensembles of neural network models
Neural Networks
RBF neural networks for classification using new Kernel functions
Neural, Parallel & Scientific Computations - Special issue: Advances in intelligent systems and applications
Application of Bayesian trained RBF networks to nonlinear time-series modeling
Signal Processing - From signal processing theory to implementation
Advanced lectures on machine learning
A novel neural network-based survival analysis model
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
Adaptive Sparseness for Supervised Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian trigonometric support vector classifier
Neural Computation
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Variational learning of clusters of undercomplete nonsymmetric independent components
The Journal of Machine Learning Research
Logistic regression and artificial neural network classification models: a methodology review
Journal of Biomedical Informatics
Translation-invariant mixture models for curve clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
An approximate analytical approach to resampling averages
The Journal of Machine Learning Research
Learning probabilistic networks
The Knowledge Engineering Review
Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
The Journal of Machine Learning Research
A tutorial on support vector regression
Statistics and Computing
Predictive automatic relevance determination by expectation propagation
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Style-based inverse kinematics
ACM SIGGRAPH 2004 Papers
Neural learning methods yielding functional invariance
Theoretical Computer Science
An asymptotic statistical theory of polynomial kernel methods
Neural Computation
A Bayesian Approach to Joint Feature Selection and Classifier Design
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shadow hybrid Monte Carlo: an efficient propagator in phase space of macromolecules
Journal of Computational Physics
Neural Networks - 2003 Special issue: Neural network analysis of complex scientific data: Astronomy and geosciences
Bayesian neural networks for nonlinear time series forecasting
Statistics and Computing
Sparse Multinomial Logistic Regression: Fast Algorithms and Generalization Bounds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Signal Processing - Content-based image and video retrieval
Preference learning with Gaussian processes
ICML '05 Proceedings of the 22nd international conference on Machine learning
Bayesian sparse sampling for on-line reward optimization
ICML '05 Proceedings of the 22nd international conference on Machine learning
Evidence Evaluation for Bayesian Neural Networks Using Contour Monte Carlo
Neural Computation
Online Model Selection Based on the Variational Bayes
Neural Computation
Predictive Approaches for Choosing Hyperparameters in Gaussian Processes
Neural Computation
Architecture-Independent Approximation of Functions
Neural Computation
Manifold Stochastic Dynamics for Bayesian Learning
Neural Computation
Robust Full Bayesian Learning for Radial Basis Networks
Neural Computation
Sequential Monte Carlo Methods to Train Neural Network Models
Neural Computation
Neural Computation
Gaussian Processes for Classification: Mean-Field Algorithms
Neural Computation
Simpler knowledge-based support vector machines
ICML '06 Proceedings of the 23rd international conference on Machine learning
Neural Networks - 2006 special issue: Earth sciences and environmental applications of computational intelligence
Bayesian testing for non-linearity in volatility modeling
Computational Statistics & Data Analysis
Computational techniques for spatial logistic regression with large data sets
Computational Statistics & Data Analysis
Variational approximations in Bayesian model selection for finite mixture distributions
Computational Statistics & Data Analysis
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
The Journal of Machine Learning Research
The Journal of Machine Learning Research
On one method of non-diagonal regularization in sparse Bayesian learning
Proceedings of the 24th international conference on Machine learning
Application of the evidence procedure to the estimation of wireless channels
EURASIP Journal on Applied Signal Processing
Clustering Based on Gaussian Processes
Neural Computation
Neural network models for conditional distribution under bayesian analysis
Neural Computation
GSHMC: An efficient method for molecular simulation
Journal of Computational Physics
Temporally correlated source separation based on variational Kalman smoother
Digital Signal Processing
Learning Bayesian networks from incomplete databases using a novel evolutionary algorithm
Decision Support Systems
Bayesian decisions with differentially fed neural networks
ICECS'03 Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal Processing
Regularity selection for effective 3D object reconstruction from a single line drawing
Pattern Recognition Letters
Probabilistic optimized ranking for multimedia semantic concept detection via RVM
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Multi-task compressive sensing with Dirichlet process priors
Proceedings of the 25th international conference on Machine learning
Learning to rank with SoftRank and Gaussian processes
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Bayesian Inference and Optimal Design for the Sparse Linear Model
The Journal of Machine Learning Research
Contrastive divergence in gaussian diffusions
Neural Computation
Hierarchical Bayesian Inference of Brain Activity
Neural Information Processing
Neural Information Processing
Pattern recognition with a Bayesian kernel combination machine
Pattern Recognition Letters
Incorporating prior model into Gaussian processes regression for WEDM process modeling
Expert Systems with Applications: An International Journal
Bagging for Gaussian process regression
Neurocomputing
Automatic EEG signal classification for epilepsy diagnosis with Relevance Vector Machines
Expert Systems with Applications: An International Journal
Artificial Intelligence in Medicine
A majorization-minimization algorithm for (multiple) hyperparameter learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Primal sparse Max-margin Markov networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Comparisons of Machine Learning Methods for Electricity Regional Reference Price Forecasting
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Human action recognition by feature-reduced Gaussian process classification
Pattern Recognition Letters
Ranking of Brain Tumour Classifiers Using a Bayesian Approach
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Bayesian inference on principal component analysis using reversible jump Markov chain Monte Carlo
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Bayesian binary kernel probit model for microarray based cancer classification and gene selection
Computational Statistics & Data Analysis
Heteroscedastic Probabilistic Linear Discriminant Analysis with Semi-supervised Extension
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Representations for action selection learning from real-time observation of task experts
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Gaussian process models of spatial aggregation algorithms
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Learning coordination classifiers
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Detection and prognostics on low-dimensional systems
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Computers and Electronics in Agriculture
International Journal of Computational Intelligence in Bioinformatics and Systems Biology
Contextual occupancy maps using Gaussian processes
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Auto claim fraud detection using Bayesian learning neural networks
Expert Systems with Applications: An International Journal
Consistent Sobolev regression via fuzzy systems with overlapping concepts
Fuzzy Sets and Systems
A novel hierarchical Bayesian HMM for multi-dimensional discrete data
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Online signature verification algorithm with a user-specific global-parameter fusion model
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Bayesian reinforcement learning in continuous pomdps with Gaussian processes
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A Survey of Statistical Network Models
Foundations and Trends® in Machine Learning
Nonlinear Models Using Dirichlet Process Mixtures
The Journal of Machine Learning Research
Sparse Kernel ridge regression using backward deletion
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
BIRD'07 Proceedings of the 1st international conference on Bioinformatics research and development
Kernel methods applied to time series forecasting
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Geometrical recombination operators for real-coded evolutionary mcmcs
Evolutionary Computation
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Generalization error of automatic relevance determination
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
An efficient search strategy for feature selection using Chow-Liu trees
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Ordinal regression with sparse Bayesian
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Bayesian inference based on stationary fokker-planck sampling
Neural Computation
Joint estimation of multiple clinical variables of neurological diseases from imaging patterns
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Large-margin classification in infinite neural networks
Neural Computation
Visualising intellectual structure of ubiquitous computing
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
An incremental Bayesian approach for training multilayer perceptrons
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
Variational Bayesian mixture of robust CCA models
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Facial expression recognition in JAFFE dataset based on Gaussian process classification
IEEE Transactions on Neural Networks
Probability models for high dynamic range imaging
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Sparse bayesian learning for identifying imaging biomarkers in AD prediction
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
The application of stochastic machine learning methods in the prediction of skin penetration
Applied Soft Computing
Dynamical systems identification using Gaussian process models with incorporated local models
Engineering Applications of Artificial Intelligence
Sparse models for gender classification
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Computer Vision and Image Understanding
Bayesian kernel projections for classification of high dimensional data
Statistics and Computing
Bayesian learning of neural networks adapted to changes of prior probabilities
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Some issues about the generalization of neural networks for time series prediction
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Multiclass Kernel-Imbedded Gaussian Processes for Microarray Data Analysis
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Weighted mutual information for feature selection
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Reversible jump MCMC simulated annealing for neural networks
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Monte Carlo inference via greedy importance sampling
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Recurrent kernel machines: Computing with infinite echo state networks
Neural Computation
Natural Language Processing (Almost) from Scratch
The Journal of Machine Learning Research
Theoretical Analysis of Bayesian Matrix Factorization
The Journal of Machine Learning Research
Nonlinear hydrological time series forecasting based on the relevance vector regression
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Analytic solution of hierarchical variational bayes in linear inverse problem
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Classification with bayesian neural networks
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
A pragmatic bayesian approach to predictive uncertainty
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
Application of bayesian techniques for MLPs to financial time series forecasting
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Gaussian process occupancy maps*
International Journal of Robotics Research
A novel learning network for option pricing with confidence interval information
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Learning multi-category classification in bayesian framework
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Pseudo-density estimation for clustering with gaussian processes
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Truncation nonlinear filters for state estimation with nonlinear inequality constraints
Automatica (Journal of IFAC)
Statistical gesture models for 3d motion capture from a library of gestures with variants
GW'09 Proceedings of the 8th international conference on Gesture in Embodied Communication and Human-Computer Interaction
Analysis of some methods for reduced rank gaussian process regression
Switching and Learning in Feedback Systems
Bayesian neural networks for prediction of protein secondary structure
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Bayesian kernel learning methods for parametric accelerated life survival analysis
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
Bayesian independent component analysis with prior constraints: an application in biosignal analysis
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
Bayesian nonlinear regression for large p small n problems
Journal of Multivariate Analysis
Optimization with Sparsity-Inducing Penalties
Foundations and Trends® in Machine Learning
A hierarchical model for ordinal matrix factorization
Statistics and Computing
Computational Statistics & Data Analysis
Learning from optically variable stars: the OMC scientific case
ADA'04 Proceedings of the 3rd international conference on Astronomical Data Analysis
Preoperative prediction of malignancy of ovarian tumors using least squares support vector machines
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
Automatica (Journal of IFAC)
Inference of disjoint linear and nonlinear sub-domains of a nonlinear mapping
Automatica (Journal of IFAC)
Deriving prediction intervals for neuro-fuzzy networks
Mathematical and Computer Modelling: An International Journal
Multi-output local Gaussian process regression: Applications to uncertainty quantification
Journal of Computational Physics
Variational multinomial logit gaussian process
The Journal of Machine Learning Research
Credit scoring models for the microfinance industry using neural networks: Evidence from Peru
Expert Systems with Applications: An International Journal
Credit risk assessment and decision making by a fusion approach
Knowledge-Based Systems
Infinite sparse threshold unit networks
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Feature analysis in tool condition monitoring: a case study in titanium machining
International Journal of Computer Applications in Technology
A hybrid intelligent system for 3D reconstruction from a single line drawing
International Journal of Computer Applications in Technology
lisa'12 Proceedings of the 26th international conference on Large Installation System Administration: strategies, tools, and techniques
Semi-parametric learning for visual odometry
International Journal of Robotics Research
Nested expectation propagation for Gaussian process classification
The Journal of Machine Learning Research
A framework for evaluating approximation methods for Gaussian process regression
The Journal of Machine Learning Research
Bayesian Canonical correlation analysis
The Journal of Machine Learning Research
Nonparametric guidance of autoencoder representations using label information
The Journal of Machine Learning Research
Exploitation of pairwise class distances for ordinal classification
Neural Computation
Pattern Recognition Letters
Random walk kernels and learning curves for Gaussian process regression on random graphs
The Journal of Machine Learning Research
An overview of bayesian methods for neural spike train analysis
Computational Intelligence and Neuroscience - Special issue on Modeling and Analysis of Neural Spike Trains
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From the Publisher:Artificial "neural networks" are now widely used as flexible models for regression classification applications, but questions remain regarding what these models mean, and how they can safely be used when training data is limited. Bayesian Learning for Neural Networks shows that Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional neural network learning methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. Use of these models in practice is made possible using Markov chain Monte Carlo techniques. Both the theoretical and computational aspects of this work are of wider statistical interest, as they contribute to a better understanding of how Bayesian methods can be applied to complex problems. Presupposing only the basic knowledge of probability and statistics, this book should be of interest to many researchers in statistics, engineering, and artificial intelligence. Software for Unix systems that implements the methods described is freely available over the Internet.