Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
Machine Learning - Special issue on inductive transfer
A framework for multiple-instance learning
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Solving the Multiple-Instance Problem: A Lazy Learning Approach
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
Supervised versus multiple instance learning: an empirical comparison
ICML '05 Proceedings of the 22nd international conference on Machine learning
KDD cup 2008 and the workshop on mining medical data
ACM SIGKDD Explorations Newsletter
Efficient Online Classification Using an Ensemble of Bayesian Linear Logistic Regressors
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Transfer Learning beyond Text Classification
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Multiple instance learning via margin maximization
Applied Numerical Mathematics
Three challenges in data mining
Frontiers of Computer Science in China
Random set framework for multiple instance learning
Information Sciences: an International Journal
Spatially regularized logistic regression for disease mapping on large moving populations
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Sparse classification for computer aided diagnosis using learned dictionaries
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
A machine-learned proactive moderation system for auction fraud detection
Proceedings of the 20th ACM international conference on Information and knowledge management
Coarse-to-fine classification via parametric and nonparametric models for computer-aided diagnosis
Proceedings of the 20th ACM international conference on Information and knowledge management
Reducing dimensionality in multiple instance learning with a filter method
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Online modeling of proactive moderation system for auction fraud detection
Proceedings of the 21st international conference on World Wide Web
HyDR-MI: A hybrid algorithm to reduce dimensionality in multiple instance learning
Information Sciences: an International Journal
Mining anatomical, physiological and pathological information from medical images
ACM SIGKDD Explorations Newsletter
Multiple instance learning via Gaussian processes
Data Mining and Knowledge Discovery
Hi-index | 0.00 |
We propose a novel Bayesian multiple instance learning (MIL) algorithm. This algorithm automatically identifies the relevant feature subset, and utilizes inductive transfer when learning multiple (conceptually related) classifiers. Experimental results indicate that the proposed MIL method is more accurate than previous MIL algorithms and selects a much smaller set of useful features. Inductive transfer further improves the accuracy of the classifier as compared to learning each task individually.