# Marc Sebban

Ontology type: schema:Person

NAME

Marc

SURNAME

Sebban

### Publications in SciGraph latest 50 shown

• 2019 Fast and Provably Effective Multi-view Classification with Landmark-Based SVM in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
• 2018-10-05 Tree-Based Cost Sensitive Methods for Fraud Detection in Imbalanced Data in ADVANCES IN INTELLIGENT DATA ANALYSIS XVII
• 2018-10-05 Online Non-linear Gradient Boosting in Multi-latent Spaces in ADVANCES IN INTELLIGENT DATA ANALYSIS XVII
• 2017 Efficient Top Rank Optimization with Gradient Boosting for Supervised Anomaly Detection in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
• 2017 Unsupervised Domain Adaptation Based on Subspace Alignment in DOMAIN ADAPTATION IN COMPUTER VISION APPLICATIONS
• 2017 Theoretical Analysis of Domain Adaptation with Optimal Transport in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
• 2016-04 A new boosting algorithm for provably accurate unsupervised domain adaptation in KNOWLEDGE AND INFORMATION SYSTEMS
• 2016 Computing Image Descriptors from Annotations Acquired from External Tools in ROBOT 2015: SECOND IBERIAN ROBOTICS CONFERENCE
• 2015 Algorithmic Robustness for Semi-Supervised $$(\epsilon , \gamma , \tau )$$ -Good Metric Learning in NEURAL INFORMATION PROCESSING
• 2015 Joint Semi-supervised Similarity Learning for Linear Classification in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
• 2014-10 Learning a priori constrained weighted majority votes in MACHINE LEARNING
• 2014 Modeling Perceptual Color Differences by Local Metric Learning in COMPUTER VISION – ECCV 2014
• 2013 Boosting for Unsupervised Domain Adaptation in ADVANCED INFORMATION SYSTEMS ENGINEERING
• 2012-10 Good edit similarity learning by loss minimization in MACHINE LEARNING
• 2011 Learning Good Edit Similarities with Generalization Guarantees in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
• 2010 Weighted Symbols-Based Edit Distance for String-Structured Image Classification in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
• 2009-04 Mining probabilistic automata: a statistical view of sequential pattern mining in MACHINE LEARNING
• 2009 Discovering Patterns in Flows: A Privacy Preserving Approach with the ACSM Prototype in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
• 2008 SEDiL: Software for Edit Distance Learning in MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES
• 2008 Melody Recognition with Learned Edit Distances in STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION
• 2007 Learning Metrics Between Tree Structured Data: Application to Image Recognition in MACHINE LEARNING: ECML 2007
• 2006 Learning Stochastic Tree Edit Distance in MACHINE LEARNING: ECML 2006
• 2006 Using Learned Conditional Distributions as Edit Distance in STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION
• 2006 A Discriminative Model of Stochastic Edit Distance in the Form of a Conditional Transducer in GRAMMATICAL INFERENCE: ALGORITHMS AND APPLICATIONS
• 2003-01-14 A Symmetric Nearest Neighbor Learning Rule in ADVANCES IN CASE-BASED REASONING
• 2003 On Boosting Improvement: Error Reduction and Convergence Speed-Up in MACHINE LEARNING: ECML 2003
• 2003 Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference in MACHINE LEARNING: ECML 2003
• 2002-09-20 Boosting Density Function Estimators in MACHINE LEARNING: ECML 2002
• 2002-07-18 Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery in PRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERY
• 2001 Prototype Selection Using Boosted Nearest-Neighbors in INSTANCE SELECTION AND CONSTRUCTION FOR DATA MINING
• 2000-05-19 Identifying and Eliminating Irrelevant Instances Using Information Theory in ADVANCES IN ARTIFICAL INTELLIGENCE
• 2000 Sharper Bounds for the Hardness of Prototype and Feature Selection in ALGORITHMIC LEARNING THEORY
• 1999 Experiments on a Representation-Independent “Top-Down and Prune” Induction Scheme in PRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERY
• 1999 Contribution of Boosting in Wrapper Models in PRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERY

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