Hierarchical mixtures of experts and the EM algorithm
Neural Computation
A Bayesian/Information Theoretic Model of Learning to Learn viaMultiple Task Sampling
Machine Learning - Special issue on inductive transfer
Machine Learning - Special issue on inductive transfer
Bayesian Classification With Gaussian Processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A general probabilistic framework for clustering individuals and objects
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Empirical Bayes for Learning to Learn
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Discriminability-Based Transfer between Neural Networks
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Regularized multi--task learning
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning Gaussian processes from multiple tasks
ICML '05 Proceedings of the 22nd international conference on Machine learning
Multi-Task Learning for Classification with Dirichlet Process Priors
The Journal of Machine Learning Research
Robust multi-task learning with t-processes
Proceedings of the 24th international conference on Machine learning
Learning and approximate inference in dynamic hierarchical models
Computational Statistics & Data Analysis
Multi-task learning for HIV therapy screening
Proceedings of the 25th international conference on Machine learning
Extracting shared subspace for multi-label classification
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
A Single Layer Perceptron Approach to Selective Multi-task Learning
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
Learning from Relevant Tasks Only
ECML '07 Proceedings of the 18th European conference on Machine Learning
An Algorithm for Transfer Learning in a Heterogeneous Environment
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Inductive transfer with context-sensitive neural networks
Machine Learning
Convex multi-task feature learning
Machine Learning
Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees
DS '08 Proceedings of the 11th International Conference on Discovery Science
Learning to Recognize Activities from the Wrong View Point
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
A convex formulation for learning shared structures from multiple tasks
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Online methods for multi-domain learning and adaptation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
An Information-Theoretic Approach for Multi-task Learning
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Semi-Supervised Multi-Task Regression
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Zero-data learning of new tasks
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Transferring multi-device localization models using latent multi-task learning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Multi-task learning for learning to rank in web search
Proceedings of the 18th ACM conference on Information and knowledge management
A multitask learning model for online pattern recognition
IEEE Transactions on Neural Networks
Transfer learning using task-level features with application to information retrieval
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A shared-subspace learning framework for multi-label classification
ACM Transactions on Knowledge Discovery from Data (TKDD)
Learning incoherent sparse and low-rank patterns from multiple tasks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Multilabel dimensionality reduction via dependence maximization
ACM Transactions on Knowledge Discovery from Data (TKDD)
Online learning for multi-task feature selection
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Relevant subtask learning by constrained mixture models
Intelligent Data Analysis
Integrating low-rank and group-sparse structures for robust multi-task learning
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Computationally Efficient Convolved Multiple Output Gaussian Processes
The Journal of Machine Learning Research
Compact coding for hyperplane classifiers in heterogeneous environment
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Multi-platform gene-expression mining and marker gene analysis
International Journal of Data Mining and Bioinformatics
Collaborative online learning of user generated content
Proceedings of the 20th ACM international conference on Information and knowledge management
Content based social behavior prediction: a multi-task learning approach
Proceedings of the 20th ACM international conference on Information and knowledge management
Multi-task learning to rank for web search
Pattern Recognition Letters
Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning
SIAM Journal on Optimization
Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks
ACM Transactions on Knowledge Discovery from Data (TKDD)
Leveraging Auxiliary Data for Learning to Rank
ACM Transactions on Intelligent Systems and Technology (TIST)
Switching and Learning in Feedback Systems
A case study on meta-generalising: a Gaussian processes approach
The Journal of Machine Learning Research
Robust multi-task feature learning
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Modeling disease progression via fused sparse group lasso
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Relational Feature Mining with Hierarchical Multitask kFOIL
Fundamenta Informaticae - Machine Learning in Bioinformatics
Tree ensembles for predicting structured outputs
Pattern Recognition
Multitask multiclass support vector machines: Model and experiments
Pattern Recognition
Multi-Task boosting by exploiting task relationships
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Efficiently learning the preferences of people
Machine Learning
Multi-Task learning using shared and task specific information
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Multitask twin support vector machines
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
Finite rank kernels for multi-task learning
Advances in Computational Mathematics
Iterative classification for multiple target attributes
Journal of Intelligent Information Systems
Multi-output least-squares support vector regression machines
Pattern Recognition Letters
Efficient online learning for multitask feature selection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Multi-task regression using minimal penalties
The Journal of Machine Learning Research
Learning output kernels for multi-task problems
Neurocomputing
Multiple task learning using iteratively reweighted least square
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Learning high-order task relationships in multi-task learning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Modeling a collection of similar regression or classification tasks can be improved by making the tasks 'learn from each other'. In machine learning, this subject is approached through 'multitask learning', where parallel tasks are modeled as multiple outputs of the same network. In multilevel analysis this is generally implemented through the mixed-effects linear model where a distinction is made between 'fixed effects', which are the same for all tasks, and 'random effects', which may vary between tasks. In the present article we will adopt a Bayesian approach in which some of the model parameters are shared (the same for all tasks) and others more loosely connected through a joint prior distribution that can be learned from the data. We seek in this way to combine the best parts of both the statistical multilevel approach and the neural network machinery. The standard assumption expressed in both approaches is that each task can learn equally well from any other task. In this article we extend the model by allowing more differentiation in the similarities between tasks. One such extension is to make the prior mean depend on higher-level task characteristics. More unsupervised clustering of tasks is obtained if we go from a single Gaussian prior to a mixture of Gaussians. This can be further generalized to a mixture of experts architecture with the gates depending on task characteristics. All three extensions are demonstrated through application both on an artificial data set and on two real-world problems, one a school problem and the other involving single-copy newspaper sales.