Matrix analysis
Topics in matrix analysis
SIAM Journal on Scientific and Statistical Computing
The ubiquitous Kronecker product
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. III: linear algebra
Ridge Regression Learning Algorithm in Dual Variables
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
On the influence of the kernel on the consistency of support vector machines
The Journal of Machine Learning Research
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Unifying collaborative and content-based filtering
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Learning from Examples as an Inverse Problem
The Journal of Machine Learning Research
Large Margin Methods for Structured and Interdependent Output Variables
The Journal of Machine Learning Research
Kernel methods for predicting protein--protein interactions
Bioinformatics
ICML '06 Proceedings of the 23rd international conference on Machine learning
Adapting ranking SVM to document retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Training linear SVMs in linear time
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A support vector method for optimizing average precision
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Shifted Kronecker Product Systems
SIAM Journal on Matrix Analysis and Applications
Learning to rank relational objects and its application to web search
Proceedings of the 17th international conference on World Wide Web
A Discriminative Kernel-Based Approach to Rank Images from Text Queries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Listwise approach to learning to rank: theory and algorithm
Proceedings of the 25th international conference on Machine learning
Label ranking by learning pairwise preferences
Artificial Intelligence
Support Vector Machines
Proceedings of the Second ACM International Conference on Web Search and Data Mining
An efficient algorithm for learning to rank from preference graphs
Machine Learning
On Pairwise Kernels: An Efficient Alternative and Generalization Analysis
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
IEEE Transactions on Pattern Analysis and Machine Intelligence
Binary Decomposition Methods for Multipartite Ranking
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Learning Preferences with Hidden Common Cause Relations
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Learning to Rank for Information Retrieval
Foundations and Trends in Information Retrieval
Efficient algorithms for ranking with SVMs
Information Retrieval
Predicting labels for dyadic data
Data Mining and Knowledge Discovery
Conditional ranking on relational data
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Fast and scalable algorithms for semi-supervised link prediction on static and dynamic graphs
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Fast active exploration for link-based preference learning using Gaussian processes
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
On Learning and Cross-Validation with Decomposed Nyström Approximation of Kernel Matrix
Neural Processing Letters
Training linear ranking SVMs in linearithmic time using red-black trees
Pattern Recognition Letters
MultiRank: co-ranking for objects and relations in multi-relational data
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Pairwise support vector machines and their application to large scale problems
The Journal of Machine Learning Research
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In domains like bioinformatics, information retrieval and social network analysis, one can find learning tasks where the goal consists of inferring a ranking of objects, conditioned on a particular target object. We present a general kernel framework for learning conditional rankings from various types of relational data, where rankings can be conditioned on unseen data objects. We propose efficient algorithms for conditional ranking by optimizing squared regression and ranking loss functions. We show theoretically, that learning with the ranking loss is likely to generalize better than with the regression loss. Further, we prove that symmetry or reciprocity properties of relations can be efficiently enforced in the learned models. Experiments on synthetic and real-world data illustrate that the proposed methods deliver state-of-the-art performance in terms of predictive power and computational efficiency. Moreover, we also show empirically that incorporating symmetry or reciprocity properties can improve the generalization performance.