Communications of the ACM - Special issue on parallelism
Classification on pairwise proximity data
Proceedings of the 1998 conference on Advances in neural information processing systems II
Pairwise Data Clustering by Deterministic Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Cluster Preserving Embedding of Nonmetric Proximity Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Convex Optimization
Learning with non-positive kernels
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Feature Space Interpretation of SVMs with Indefinite Kernels
IEEE Transactions on Pattern Analysis and Machine Intelligence
Support vector machines for dyadic data
Neural Computation
Local similarity discriminant analysis
Proceedings of the 24th international conference on Machine learning
Training SVM with indefinite kernels
Proceedings of the 25th international conference on Machine learning
Similarity-based Classification: Concepts and Algorithms
The Journal of Machine Learning Research
A Reformulation of Support Vector Machines for General Confidence Functions
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Online multiple kernel learning: algorithms and mistake bounds
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
Classification of microorganisms via Raman spectroscopy using Gaussian processes
Proceedings of the 32nd DAGM conference on Pattern recognition
The Journal of Machine Learning Research
Multi-task regularization of generative similarity models
SIMBAD'11 Proceedings of the First international conference on Similarity-based pattern recognition
LoadIQ: learning to identify workload phases from a live storage trace
HotStorage'12 Proceedings of the 4th USENIX conference on Hot Topics in Storage and File Systems
Gender classification from unaligned facial images using support subspaces
Information Sciences: an International Journal
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Online Multiple Kernel Classification
Machine Learning
Similarity-based clustering by left-stochastic matrix factorization
The Journal of Machine Learning Research
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Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similarities. These indefinite kernels can be problematic for standard kernel-based algorithms as the optimization problems become non-convex and the underlying theory is invalidated. In order to adapt kernel methods for similarity-based learning, we introduce a method that aims to simultaneously find a reproducing kernel Hilbert space based on the given similarities and train a classifier with good generalization in that space. The method is formulated as a convex optimization problem. We propose a simplified version that can reduce overfitting and whose associated convex conic program can be solved efficiently. We compare the proposed simplified version with six other methods on a collection of real data sets.