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COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Machine Learning - Special issue on inductive transfer
Prediction with Gaussian processes: from linear regression to linear prediction and beyond
Proceedings of the NATO Advanced Study Institute on Learning in graphical models
Using the Fisher Kernel Method to Detect Remote Protein Homologies
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
Learning Gaussian processes from multiple tasks
ICML '05 Proceedings of the 22nd international conference on Machine learning
Constructing informative priors using transfer learning
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Multi-Task Learning for Classification with Dirichlet Process Priors
The Journal of Machine Learning Research
Convex multi-task feature learning
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ACM Transactions on Graphics (TOG)
A convex formulation for learning shared structures from multiple tasks
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
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ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
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Neural Computation
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ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Relaxed Transfer of Different Classes via Spectral Partition
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Semi-Supervised Multi-Task Regression
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Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-view transfer learning with a large margin approach
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-task learning to rank for web search
Pattern Recognition Letters
Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks
ACM Transactions on Knowledge Discovery from Data (TKDD)
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Pairwise cross-domain factor model for heterogeneous transfer ranking
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Extensions of the informative vector machine
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Expert Systems with Applications: An International Journal
Using previous models to bias structural learning in the hierarchical boa
Evolutionary Computation
Sentiment detection with auxiliary data
Information Retrieval
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
Double-bootstrapping source data selection for instance-based transfer learning
Pattern Recognition Letters
Multiple task learning using iteratively reweighted least square
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper describes an efficient method for learning the parameters of a Gaussian process (GP). The parameters are learned from multiple tasks which are assumed to have been drawn independently from the same GP prior. An efficient algorithm is obtained by extending the informative vector machine (IVM) algorithm to handle the multi-task learning case. The multi-task IVM (MTIVM) saves computation by greedily selecting the most informative examples from the separate tasks. The MT-IVM is also shown to be more efficient than random sub-sampling on an artificial data-set and more effective than the traditional IVM in a speaker dependent phoneme recognition task.