Learning internal representations
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Machine Learning - Special issue on inductive transfer
Learning to learn
Feature Selection and Dualities in Maximum Entropy Discrimination
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Learning the Kernel Matrix with Semi-Definite Programming
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
A model of inductive bias learning
Journal of Artificial Intelligence Research
Discriminant kernel and regularization parameter learning via semidefinite programming
Proceedings of the 24th international conference on Machine learning
Nonlinear adaptive distance metric learning for clustering
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-class Discriminant Kernel Learning via Convex Programming
The Journal of Machine Learning Research
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
Inductive transfer with context-sensitive neural networks
Machine Learning
Convex multi-task feature learning
Machine Learning
Transfer learning for collaborative filtering via a rating-matrix generative model
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC)
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Heterogeneous cross domain ranking in latent space
Proceedings of the 18th ACM conference on Information and knowledge management
On multiple kernel learning with multiple labels
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Image transformation: inductive transfer between multiple tasks having multiple outputs
Canadian AI'08 Proceedings of the Canadian Society for computational studies of intelligence, 21st conference on Advances in artificial intelligence
L2 regularization for learning kernels
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
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
Multitask Sparsity via Maximum Entropy Discrimination
The Journal of Machine Learning Research
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
The Journal of Machine Learning Research
Knowledge transfer across multilingual corpora via latent topics
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Using previous models to bias structural learning in the hierarchical boa
Evolutionary Computation
Feature selection for dimensionality reduction
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
Algorithms for learning kernels based on centered alignment
The Journal of Machine Learning Research
Multi-kernel multi-label learning with max-margin concept network
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Short-term prediction of air pollution in macau using support vector machines
Journal of Control Science and Engineering - Special issue on Advanced Control in Micro-/Nanosystems
Transfer Learning from Unlabeled Data via Neural Networks
Neural Processing Letters
Sentiment and topic analysis on social media: a multi-task multi-label classification approach
Proceedings of the 5th Annual ACM Web Science Conference
Efficient online learning for multitask feature selection
ACM Transactions on Knowledge Discovery from Data (TKDD)
Multi-view maximum entropy discrimination
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Multi-task learning with one-class SVM
Neurocomputing
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We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is advantageous when multiple classification tasks and differently labeled datasets exist over a common input space. Different datasets can mutually reinforce a common choice of representation or relevant features for their various classifiers. We derive a multi-task representation learning approach using the maximum entropy discrimination formalism. The resulting convex algorithms maintain the global solution properties of support vector machines. However, in addition to multiple SVM classification/regression parameters they also jointly estimate an optimal subset of features or optimal combination of kernels. Experiments are shown on standardized datasets.