Machine Learning - Special issue on inductive transfer
Prediction with Gaussian processes: from linear regression to linear prediction and beyond
Learning in graphical models
Text Categorization Based on Regularized Linear Classification Methods
Information Retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
The Journal of Machine Learning Research
Task clustering and gating for bayesian multitask learning
The Journal of Machine Learning Research
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Regularized multi--task learning
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning to learn with the informative vector machine
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Learning a kernel function for classification with small training samples
ICML '06 Proceedings of the 23rd international conference on Machine learning
Constructing informative priors using transfer learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Collaborative ordinal regression
ICML '06 Proceedings of the 23rd international conference on Machine learning
Multi-Task Learning for Classification with Dirichlet Process Priors
The Journal of Machine Learning Research
Learning a meta-level prior for feature relevance from multiple related tasks
Proceedings of the 24th international conference on Machine learning
Robust multi-task learning with t-processes
Proceedings of the 24th international conference on Machine learning
Efficient bayesian hierarchical user modeling for recommendation system
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Multi-task learning for HIV therapy screening
Proceedings of the 25th international conference on Machine learning
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 Improved Multi-task Learning Approach with Applications in Medical Diagnosis
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Kernel-Based Inductive Transfer
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Convex multi-task feature learning
Machine Learning
Flexible latent variable models for multi-task learning
Machine Learning
Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees
DS '08 Proceedings of the 11th International Conference on Discovery Science
Multitask visual learning using genetic programming
Evolutionary Computation
A convex formulation for learning shared structures from multiple tasks
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Large-scale collaborative prediction using a nonparametric random effects model
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Context Dependent Movie Recommendations Using a Hierarchical Bayesian Model
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
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
Hierarchical Bayesian domain adaptation
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Multi-task learning for learning to rank in web search
Proceedings of the 18th ACM conference on Information and knowledge management
IEEE Transactions on Signal Processing
Transfer learning using task-level features with application to information retrieval
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Automatic Choice of Control Measurements
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Bayesian multitask learning with latent hierarchies
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Learning incoherent sparse and low-rank patterns from multiple tasks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Learning common grammar from multilingual corpus
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Concept classification with Bayesian multi-task learning
CN '10 Proceedings of the NAACL HLT 2010 First Workshop on Computational Neurolinguistics
Shift-invariant grouped multi-task learning for Gaussian processes
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Relevant subtask learning by constrained mixture models
Intelligent Data Analysis
Multi-agent learning by distributed feature extraction
ALAMAS'05/ALAMAS'06/ALAMAS'07 Proceedings of the 5th , 6th and 7th European conference on Adaptive and learning agents and multi-agent systems: adaptation and multi-agent learning
Neurocomputing
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
Conditional graphical models for protein structure prediction
Conditional graphical models for protein structure prediction
Multi-platform gene-expression mining and marker gene analysis
International Journal of Data Mining and Bioinformatics
Multi-task learning to rank for web search
Pattern Recognition Letters
Theoretical Analysis of Bayesian Matrix Factorization
The Journal of Machine Learning Research
The Journal of Machine Learning Research
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)
Improved machine learning models for predicting selective compounds
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Expert Systems with Applications: An International Journal
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
Kernels for Vector-Valued Functions: A Review
Foundations and Trends® in Machine Learning
Fast multi-task learning for query spelling correction
Proceedings of the 21st ACM international conference on Information and knowledge management
Sparse gaussian processes for multi-task learning
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
Iterative classification for multiple target attributes
Journal of Intelligent Information Systems
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
Proceedings of the 7th ACM international conference on Web search and data mining
Multi-stage multi-task feature learning
The Journal of Machine Learning Research
| Hi-index | 0.01 |
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equivalence between parametric linear models and nonparametric Gaussian processes (GPs). The resulting models can be learned easily via an EM-algorithm. Empirical studies on multi-label text categorization suggest that the presented models allow accurate solutions of these multi-task problems.