An Experimental and Theoretical Comparison of Model SelectionMethods
Machine Learning - Special issue on the eighth annual conference on computational learning theory, (COLT '95)
Generalization in decision trees and DNF: does size matter?
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Improved Generalization Through Explicit Optimization of Margins
Machine Learning
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Learning in Neural Networks: Theoretical Foundations
Learning in Neural Networks: Theoretical Foundations
Model Selection and Error Estimation
Machine Learning
Using output codes to boost multiclass learning problems
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
IEEE Transactions on Information Theory
Structural risk minimization over data-dependent hierarchies
IEEE Transactions on Information Theory
Rademacher penalties and structural risk minimization
IEEE Transactions on Information Theory
Rademacher averages and phase transitions in Glivenko-Cantelli classes
IEEE Transactions on Information Theory
An introduction to boosting and leveraging
Advanced lectures on machine learning
Quantum optimization for training support vector machines
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
Data-dependent margin-based generalization bounds for classification
The Journal of Machine Learning Research
Greedy algorithms for classification—consistency, convergence rates, and adaptivity
The Journal of Machine Learning Research
Generalization error bounds for Bayesian mixture algorithms
The Journal of Machine Learning Research
On the rate of convergence of regularized boosting classifiers
The Journal of Machine Learning Research
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
Distance--Based Classification with Lipschitz Functions
The Journal of Machine Learning Research
On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition
The Journal of Machine Learning Research
Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees
The Journal of Machine Learning Research
Diffusion Kernels on Statistical Manifolds
The Journal of Machine Learning Research
On the Generalization Ability of GRLVQ Networks
Neural Processing Letters
Sparse Multinomial Logistic Regression: Fast Algorithms and Generalization Bounds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maximal margin classification for metric spaces
Journal of Computer and System Sciences - Special issue: Learning theory 2003
Simpler knowledge-based support vector machines
ICML '06 Proceedings of the 23rd international conference on Machine learning
Margin-based active learning for LVQ networks
Neurocomputing
On nonparametric classification with missing covariates
Journal of Multivariate Analysis
Nonparametric Quantile Estimation
The Journal of Machine Learning Research
Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss
The Journal of Machine Learning Research
Learnability of Gaussians with Flexible Variances
The Journal of Machine Learning Research
Sample compression bounds for decision trees
Proceedings of the 24th international conference on Machine learning
Complexity of pattern classes and the Lipschitz property
Theoretical Computer Science
Incentive compatible regression learning
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
The value of agreement a new boosting algorithm
Journal of Computer and System Sciences
A theory of learning with similarity functions
Machine Learning
Estimating labels from label proportions
Proceedings of the 25th international conference on Machine learning
SVM optimization: inverse dependence on training set size
Proceedings of the 25th international conference on Machine learning
Tailoring density estimation via reproducing kernel moment matching
Proceedings of the 25th international conference on Machine learning
Learning Similarity with Operator-valued Large-margin Classifiers
The Journal of Machine Learning Research
A Hilbert Space Embedding for Distributions
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
Catenary Support Vector Machines
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Support Vector Machines, Data Reduction, and Approximate Kernel Matrices
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Generalization Bounds for K-Dimensional Coding Schemes in Hilbert Spaces
ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory
Structural Support Vector Machine
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Learning from Multiple Sources
The Journal of Machine Learning Research
Boosting method for local learning in statistical pattern recognition
Neural Computation
Reducing mechanism design to algorithm design via machine learning
Journal of Computer and System Sciences
Learning rates of gradient descent algorithm for classification
Journal of Computational and Applied Mathematics
Error bounds of multi-graph regularized semi-supervised classification
Information Sciences: an International Journal
Transfer bounds for linear feature learning
Machine Learning
Multiple indefinite kernel learning with mixed norm regularization
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Generalization analysis of listwise learning-to-rank algorithms
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Robust support vector machine training via convex outlier ablation
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Capacity Control for Partially Ordered Feature Sets
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Learning to Rank for Information Retrieval
Foundations and Trends in Information Retrieval
Explanation-based feature construction
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Error bounds of decision templates and support vector machines in decision fusion
International Journal of Knowledge Engineering and Soft Data Paradigms
Transductive Rademacher complexity and its applications
Journal of Artificial Intelligence Research
Large margin Boltzmann machines
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Learning SVMs from Sloppily Labeled Data
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
A discriminative model for semi-supervised learning
Journal of the ACM (JACM)
Adaptive relevance matrices in learning vector quantization
Neural Computation
Robustness and Regularization of Support Vector Machines
The Journal of Machine Learning Research
Margin-based Ranking and an Equivalence between AdaBoost and RankBoost
The Journal of Machine Learning Research
Estimating Labels from Label Proportions
The Journal of Machine Learning Research
Classification Using Geometric Level Sets
The Journal of Machine Learning Research
Maximum Relative Margin and Data-Dependent Regularization
The Journal of Machine Learning Research
Deriving the kernel from training data
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Transductive rademacher complexity and its applications
COLT'07 Proceedings of the 20th annual conference on Learning theory
How good is a kernel when used as a similarity measure?
COLT'07 Proceedings of the 20th annual conference on Learning theory
COLT'07 Proceedings of the 20th annual conference on Learning theory
Using unsupervised analysis to constrain generalization bounds for support vector classifiers
IEEE Transactions on Neural Networks
Gradient descent optimization of smoothed information retrieval metrics
Information Retrieval
Incentive compatible regression learning
Journal of Computer and System Sciences
The Journal of Machine Learning Research
Rademacher chaos complexities for learning the kernel problem
Neural Computation
Generalized derivative based kernelized learning vector quantization
IDEAL'10 Proceedings of the 11th international conference on Intelligent data engineering and automated learning
On the power of topological kernel in microarray-based detection of cancer
IDEAL'10 Proceedings of the 11th international conference on Intelligent data engineering and automated learning
Rademacher complexity and grammar induction algorithms: what it may (not) tell us
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
A unifying view of multiple kernel learning
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
K-dimensional coding schemes in Hilbert spaces
IEEE Transactions on Information Theory
Sparse Semi-supervised Learning Using Conjugate Functions
The Journal of Machine Learning Research
On Convergence of Kernel Learning Estimators
SIAM Journal on Optimization
Maximal Discrepancy for Support Vector Machines
Neurocomputing
A novel multi-view classifier based on Nyström approximation
Expert Systems with Applications: An International Journal
Support Vector Machines with the Ramp Loss and the Hard Margin Loss
Operations Research
A novel multi-view learning developed from single-view patterns
Pattern Recognition
lp-Norm Multiple Kernel Learning
The Journal of Machine Learning Research
The Journal of Machine Learning Research
A general framework for dimensionality reduction for large data sets
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
Transfer learning with adaptive regularizers
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Pattern Recognition Letters
The consistency analysis of coefficient regularized classification with convex loss
WSEAS Transactions on Mathematics
The rademacher complexity of linear transformation classes
COLT'06 Proceedings of the 19th annual conference on Learning Theory
The value of agreement, a new boosting algorithm
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Generalization error bounds using unlabeled data
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Generalization behaviour of alkemic decision trees
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
A general framework for dimensionality-reducing data visualization mapping
Neural Computation
Learning vector quantization classification with local relevance determination for medical data
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Generalization bounds for subspace selection and hyperbolic PCA
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
Multi-view laplacian support vector machines
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II
Structured sparsity and generalization
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Bound the learning rates with generalized gradients
WSEAS Transactions on Signal Processing
Generalization error bounds for the logical analysis of data
Discrete Applied Mathematics
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Sample complexity of linear learning machines with different restrictions over weights
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Application of integral operator for regularized least-square regression
Mathematical and Computer Modelling: An International Journal
Learning linear and kernel predictors with the 0-1 loss function
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Fast Structured Prediction Using Large Margin Sigmoid Belief Networks
International Journal of Computer Vision
Learning Kernel-Based Halfspaces with the 0-1 Loss
SIAM Journal on Computing
Regularization techniques for learning with matrices
The Journal of Machine Learning Research
Multisource domain adaptation and its application to early detection of fatigue
ACM Transactions on Knowledge Discovery from Data (TKDD) - Special Issue on the Best of SIGKDD 2011
Learning the coordinate gradients
Advances in Computational Mathematics
An alternative approach to avoid overfitting for surrogate models
Proceedings of the Winter Simulation Conference
A Computational Learning Theory of Active Object Recognition Under Uncertainty
International Journal of Computer Vision
Effect on generalization of using relational information in list-wise algorithms
ICPCA/SWS'12 Proceedings of the 2012 international conference on Pervasive Computing and the Networked World
Learning with boundary conditions
Neural Computation
Querying discriminative and representative samples for batch mode active learning
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Multiple spectral kernel learning and a gaussian complexity computation
Neural Computation
On the convergence rate of lp-norm multiple kernel learning
The Journal of Machine Learning Research
Multi-instance learning with any hypothesis class
The Journal of Machine Learning Research
PAC-bayes bounds with data dependent priors
The Journal of Machine Learning Research
Eigenvalues perturbation of integral operator for kernel selection
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Universal learning using free multivariate splines
Neurocomputing
Multi class learning with individual sparsity
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers
Pattern Recognition Letters
Machine learning with operational costs
The Journal of Machine Learning Research
Distribution-dependent sample complexity of large margin learning
The Journal of Machine Learning Research
Learning bilinear model for matching queries and documents
The Journal of Machine Learning Research
Maximum volume clustering: a new discriminative clustering approach
The Journal of Machine Learning Research
Guaranteed classification via regularized similarity learning
Neural Computation
Learning vector quantization for (dis-)similarities
Neurocomputing
Approximation and Estimation Bounds for Subsets of Reproducing Kernel Kreĭn Spaces
Neural Processing Letters
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We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we prove general risk bounds in terms of these complexities. We consider function classes that can be expressed as combinations of functions from basis classes and show how the Rademacher and Gaussian complexities of such a function class can be bounded in terms of the complexity of the basis classes. We give examples of the application of these techniques in finding data-dependent risk bounds for decision trees, neural networks and support vector machines.