Readings in speech recognition
Approximation alogorithms for the maximum acyclic subgraph problem
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Machine Learning
Adjustment Learning and Relevant Component Analysis
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Constrained K-means Clustering with Background Knowledge
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A Generalized Representer Theorem
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Convex Optimization
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
Integrating constraints and metric learning in semi-supervised clustering
ICML '04 Proceedings of the twenty-first international conference on Machine learning
The Journal of Machine Learning Research
The Amsterdam Library of Object Images
International Journal of Computer Vision
Pruning Training Sets for Learning of Object Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Large Scale Multiple Kernel Learning
The Journal of Machine Learning Research
Information-theoretic metric learning
Proceedings of the 24th international conference on Machine learning
Multiclass multiple kernel learning
Proceedings of the 24th international conference on Machine learning
Consistency of the Group Lasso and Multiple Kernel Learning
The Journal of Machine Learning Research
Avoiding Boosting Overfitting by Removing Confusing Samples
ECML '07 Proceedings of the 18th European conference on Machine Learning
Partial order embedding with multiple kernels
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Semantic Annotation and Retrieval of Music and Sound Effects
IEEE Transactions on Audio, Speech, and Language Processing
Music retagging using label propagation and robust principal component analysis
Proceedings of the 21st international conference companion on World Wide Web
Online multi-modal distance learning for scalable multimedia retrieval
Proceedings of the sixth ACM international conference on Web search and data mining
Combining embedded accelerometers with computer vision for recognizing food preparation activities
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Online multimodal deep similarity learning with application to image retrieval
Proceedings of the 21st ACM international conference on Multimedia
Neighborhood Correlation Analysis for Semi-paired Two-View Data
Neural Processing Letters
Multi-modal distance metric learning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In many applications involving multi-media data, the definition of similarity between items is integral to several key tasks, including nearest-neighbor retrieval, classification, and recommendation. Data in such regimes typically exhibits multiple modalities, such as acoustic and visual content of video. Integrating such heterogeneous data to form a holistic similarity space is therefore a key challenge to be overcome in many real-world applications. We present a novel multiple kernel learning technique for integrating heterogeneous data into a single, unified similarity space. Our algorithm learns an optimal ensemble of kernel transformations which conform to measurements of human perceptual similarity, as expressed by relative comparisons. To cope with the ubiquitous problems of subjectivity and inconsistency in multi-media similarity, we develop graph-based techniques to filter similarity measurements, resulting in a simplified and robust training procedure.