Learning and evaluating classifiers under sample selection bias
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Multi-Task Learning for Classification with Dirichlet Process Priors
The Journal of Machine Learning Research
The class imbalance problem: A systematic study
Intelligent Data Analysis
The foundations of cost-sensitive learning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Model selection under covariate shift
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Making generative classifiers robust to selection bias
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-task learning for HIV therapy screening
Proceedings of the 25th international conference on Machine learning
Knowledge transfer via multiple model local structure mapping
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Spectral domain-transfer learning
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Categorizing and mining concept drifting data streams
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Actively Transfer Domain Knowledge
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Pool-Based Agnostic Experiment Design in Linear Regression
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Sample Selection Bias Correction Theory
ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory
Email Spam Filtering: A Systematic Review
Foundations and Trends in Information Retrieval
Domain adaptation of information extraction models
ACM SIGMOD Record
Latent space domain transfer between high dimensional overlapping distributions
Proceedings of the 18th international conference on World wide web
Pool-based active learning in approximate linear regression
Machine Learning
Cross domain distribution adaptation via kernel mapping
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Heterogeneous cross domain ranking in latent space
Proceedings of the 18th ACM conference on Information and knowledge management
Large margin transductive transfer learning
Proceedings of the 18th ACM conference on Information and knowledge management
A risk minimization framework for domain adaptation
Proceedings of the 18th ACM conference on Information and knowledge management
Density Ratio Estimation: A New Versatile Tool for Machine Learning
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Learning Algorithms for Domain Adaptation
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Domain adaptive bootstrapping for named entity recognition
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
A Least-squares Approach to Direct Importance Estimation
The Journal of Machine Learning Research
Discriminative Learning Under Covariate Shift
The Journal of Machine Learning Research
A framework for modeling positive class expansion with single snapshot
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Bayesian multitask learning with latent hierarchies
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
A robust semi-supervised classification method for transfer learning
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Semi-supervised ranking for document retrieval
Computer Speech and Language
Domain adaptation by constraining inter-domain variability of latent feature representation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Transfer learning through domain adaptation
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
Localized factor models for multi-context recommendation
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
A unifying view on dataset shift in classification
Pattern Recognition
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
On the usefulness of similarity based projection spaces for transfer learning
SIMBAD'11 Proceedings of the First international conference on Similarity-based pattern recognition
Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset
Proceedings of the 20th ACM international conference on Information and knowledge management
Transfer learning for cross-company software defect prediction
Information and Software Technology
Pairwise cross-domain factor model for heterogeneous transfer ranking
Proceedings of the fifth ACM international conference on Web search and data mining
Robust Video Content Analysis via Transductive Learning
ACM Transactions on Intelligent Systems and Technology (TIST)
Flexible sample selection strategies for transfer learning in ranking
Information Processing and Management: an International Journal
Distance metric learning under covariate shift
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Visual knowledge transfer among multiple cameras for people counting with occlusion handling
Proceedings of the 20th ACM international conference on Multimedia
Cross-Database transfer learning via learnable and discriminant error-correcting output codes
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Neural Computation
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We address classification problems for which the training instances are governed by a distribution that is allowed to differ arbitrarily from the test distribution---problems also referred to as classification under covariate shift. We derive a solution that is purely discriminative: neither training nor test distribution are modeled explicitly. We formulate the general problem of learning under covariate shift as an integrated optimization problem. We derive a kernel logistic regression classifier for differing training and test distributions.