Matrix analysis
Least Squares Support Vector Machine Classifiers
Neural Processing Letters
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
The Case against Accuracy Estimation for Comparing Induction Algorithms
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Sparse Greedy Matrix Approximation for Machine Learning
ICML '00 Proceedings of the Seventeenth 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
An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
Everything old is new again: a fresh look at historical approaches in machine learning
Everything old is new again: a fresh look at historical approaches in machine learning
Benchmarking Least Squares Support Vector Machine Classifiers
Machine Learning
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
In Defense of One-Vs-All Classification
The Journal of Machine Learning Research
SVM vs Regularized Least Squares Classification
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Using AUC and Accuracy in Evaluating Learning Algorithms
IEEE Transactions on Knowledge and Data Engineering
A support vector method for multivariate performance measures
ICML '05 Proceedings of the 22nd international conference on Machine learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Training linear SVMs in linear time
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A Unifying View of Sparse Approximate Gaussian Process Regression
The Journal of Machine Learning Research
Value Regularization and Fenchel Duality
The Journal of Machine Learning Research
Magnitude-preserving ranking algorithms
Proceedings of the 24th international conference on Machine learning
The Need for Open Source Software in Machine Learning
The Journal of Machine Learning Research
Efficient AUC Maximization with Regularized Least-Squares
Proceedings of the 2008 conference on Tenth Scandinavian Conference on Artificial Intelligence: SCAI 2008
A Sparse Regularized Least-Squares Preference Learning Algorithm
Proceedings of the 2008 conference on Tenth Scandinavian Conference on Artificial Intelligence: SCAI 2008
An alternative ranking problem for search engines
WEA'07 Proceedings of the 6th international conference on Experimental algorithms
Ranking and scoring using empirical risk minimization
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Stability and generalization of bipartite ranking algorithms
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Permutation tests for classification
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Regularized least-squares for parse ranking
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
Graph-Based Semi-Supervised Learning and Spectral Kernel Design
IEEE Transactions on Information Theory
Input space versus feature space in kernel-based methods
IEEE Transactions on Neural Networks
Efficient hold-out for subset of regressors
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Conditional ranking on relational data
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Computational Statistics & Data Analysis
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
An improved training algorithm for the linear ranking support vector machine
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
Leveraging Auxiliary Data for Learning to Rank
ACM Transactions on Intelligent Systems and Technology (TIST)
Generic subset ranking using binary classifiers
Theoretical Computer Science
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Motivated by chemical applications, we revisit and extend a family of positive definite kernels for graphs based on the detection of common subtrees, initially proposed by Ramon and Gärtner (Proceedings of the first international workshop on mining ...