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Soft Margins for AdaBoost
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Gunnar Rätsch, Ph.D.
Publications
Using Support Vector Machines for Time Series Prediction
Soft Margins for AdaBoost
An improvement of AdaBoost to avoid overfitting
Ensemble Learning Methods for Classification
Using Support Vector Machines for Time Series Prediction
An asymptotic analysis of AdaBoost in the binary classification case
Kernel PCA Pattern Reconstruction via Approximate Pre-Images
Fisher Discriminant Analysis with Kernels
Linear Programs for Automatic Accuracy Control in Regression
Input Space vs. Feature Space in Kernel-Based Methods
Engineering Support Vector Machine Kernel That Recognize Translation Initiation Sites in DNA
Aspekte der Flexibilisierung von Systemen für den Hardwaretest
Regularizing AdaBoost
Kernel PCA and De-Noising in Feature Spaces
Robust Boosting via Convex Optimization
A mathematical programming approach to the Kernel Fisher algorithm
An Introduction to Kernel-based Learning Algorithms
An Arcing algorithm with an intuitive learning control parameter
On the Convergence of Leveraging
Soft Margins for AdaBoost
Marginal Boosting
Learning To Predict the Leave-one-out Error of Kernel based classifiers
SVM and Boosting: One Class
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
Barrier Boosting
Analysis of Nonstationary Time Series by Mixtures of Self-Organizing Predictors
Learning Discriminative and Invariant Nonlinear Features
An asymptotical Analysis and Improvement of AdaBoost in the binary classification case
A Non-Intrusive Monitoring System for Household Electric Appliances with Inverters
Trends in Boosting Research and Applications
Robust Ensemble Learning
Robust Ensemble Learning for Data Mining
$\nu $-Arc: Ensemble Learning in the Presence of Outliers
Invariant Feature Extraction and Classification in Kernel Spaces
Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites in DNA
Robustes Boosting durch konvexe Optimierung
Marginal Boosting
New Methods for Splice Site Recognition
A New Discriminative Kernel from Probabilistic Models
On the Convergence of Leveraging
A New Discriminative Kernel from Probabilistic Models
Active Learning in the Drug Discovery Process
Constructing Boosting Algorithms from SVMs: an Application to One-Class Classification
Image Reconstruction by Linear Programming
Robust Multi-Class Boosting
Constructing Descriptive and Discriminative Non-Linear Features: Rayleigh Coefficients in Kernel Feature Space
Adapting Codes and Embeddings for Polychotomies
Active Learning with SVMs in the Drug Discovery Process
An Introduction to Boosting and Leveraging
RASE: Recognition of alternatively Spliced Exons in C. elegans
Learning interpretable SVMs for biological sequence classification
Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection
Large Scale Genomic Sequence SVM Classifiers
Efficient Margin Maximization with Boosting
Totally Corrective Boosting Algorithms that Maximize the Margin
Learning interpretable SVMs for biological sequence classification
ARTS: Accurate Recognition of Transcription Starts in Human
Classifying 'Drug-likeness' with Kernel-Based Learning Methods
A general and efficient multiple kernel learning algorithm
Image reconstruction by linear programming
Large scale multiple kernel learning
Improving the C. elegans genome annotation using machine learning
New Problems and Methods in Computational Biology
PALMA: mRNA to Genome Alignments using Large Margin Algorithms
Common Sequence Polymorphisms Shaping Genetic Diversity in Arabidopsis thaliana
Boosting Algorithms for Maximizing the Soft Margin
Transcript Normalization and Segmentation of Tiling Array Data
Accurate splice site prediction using support vector machines
New Problems and Methods in Computational Biology
Large Scale Learning with String Kernels
PALMA: Perfect Alignments using Large Margin Algorithms
QPALMA: Optimal Spliced Alignments of Short Sequence Reads
Detecting Polymorphic Regions in Arabidopsis thaliana with Resequencing Microarrays
POIMs: Positional Oligomer Importance Matrices - Understanding Support Vector Machine Based Signal Detectors
Prototype Classification: Insights from Machine Learning
Accurate Splice Site Detection for Caenorhabditis elegans
Dual roles of the nuclear cap binding complex and SERRATE in pre-mRNA splicing and microRNA processing in Arabidopsis thaliana
KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences
At-TAX: a whole genome tiling array resource for developmental expression analysis and transcript identification in Arabidopsis thaliana
Support Vector Machines and Kernels for Computational Biology
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
Zur Beurteilung des Fraud-Risikos im Rahmen der Abschlussprüfung
An empirical Analysis of Domain Adaptation Algorithms
nGASP – the nematode genome annotation assessment project
mGene.web: a web service for accurate computational gene finding
QPALMA:: Optimal Spliced Alignments of Short Sequence Reads
The Feature Importance Ranking Measure
mGene: Accurate SVM-Based Gene Finding with an Application to Nematode Genomes
Large Scale Hidden Semi-Markov SVMs
Leveraging Sequence Classification by Taxonomy-based Multitask Learning
Statistical Tests for Detecting Differential RNA-Transcript Expression from Read Counts
The SHOGUN Machine Learning Toolbox
Modern Methods for Transcriptome Reconstruction
rQuant.web: a tool for RNA-Seq-based transcript quantitation
Novel Machine Learning Methods for MHC Class I Binding Prediction
Exploiting Physico-Chemical Properties in String Kernels
Inferring Latent Task Structure for Multi-Task Learning by Multiple Kernel Learning
Global effects of the small RNA biogenesis machinery on the Arabidopsis thaliana transcriptome
A Spatial and Temporal Map of C. elegans Gene Expression
A receptor-type guanylate cyclase is required for carbon dioxide sensation by C. elegans
Integrative Analysis of the Caenorhabditis elegans Genome by the modENCODE Project
RNA-Seq Read Alignments with PALMapper
Detection of Alternative Splicing in Arabidopsis thaliana from Whole-Genome Tiling Arrays with Support Vector Machines
RNA-Seq analysis in mutant zebrafish reveals role of U1C protein in alternative splicing regulation
Multitask Learning in Computational Biology
Multiple reference genomes and transcriptomes for Arabidopsis thaliana.
Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation
Multiple insert size paired-end sequencing for deconvolution of complex transcriptomes
HnRNP L and L-like cooperate in multiple-exon regulation of CD45 alternative splicing
Cohesin rings devoid of Scc3 and Pds5 maintain their stable association with the DNA.
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G Rätsch, T Onoda, and K Müller
(
2001
)
Soft Margins for AdaBoost
Machine Learning, 42(3):287-320.
Note
also NeuroCOLT Technical Report NC-TR-1998-021
What's New?
Gunnar Rätsch, Ph.D.
Publications
Using Support Vector Machines for Time Series Prediction
