Olivier Chapelle
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Olivier Chapellecomputer-science Degrees
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Machine Learning
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Computer Science
Olivier Chapelle's Degrees
- PhD Computer Science Carnegie Mellon University
- Masters Computer Science Université catholique de Louvain
- Bachelors Computer Science Université catholique de Louvain
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(Suggest an Edit or Addition)Olivier Chapelle's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Semi-Supervised Learning (2006) (2560)
- Choosing Multiple Parameters for Support Vector Machines (2002) (2336)
- Support vector machines for histogram-based image classification (1999) (1525)
- An Empirical Evaluation of Thompson Sampling (2011) (1234)
- Feature Selection for SVMs (2000) (1167)
- Semi-Supervised Classification by Low Density Separation (2005) (930)
- Training a Support Vector Machine in the Primal (2007) (867)
- Expected reciprocal rank for graded relevance (2009) (815)
- Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews] (2009) (634)
- Yahoo! Learning to Rank Challenge Overview (2010) (546)
- A dynamic bayesian network click model for web search ranking (2009) (538)
- Cluster Kernels for Semi-Supervised Learning (2002) (521)
- Introduction to Semi-Supervised Learning (2006) (476)
- Optimization Techniques for Semi-Supervised Support Vector Machines (2008) (447)
- The 2005 PASCAL Visual Object Classes Challenge (2005) (443)
- Model Selection for Support Vector Machines (1999) (408)
- A reliable effective terascale linear learning system (2011) (368)
- Feature selection for support vector machines by means of genetic algorithm (2003) (356)
- Simple and Scalable Response Prediction for Display Advertising (2014) (325)
- Large-scale kernel machines (2007) (314)
- Building Support Vector Machines with Reduced Classifier Complexity (2006) (310)
- Support Vector Machine Solvers (2007) (297)
- Efficient algorithms for ranking with SVMs (2010) (278)
- SVMs for Histogram Based Image Classification (1999) (274)
- Label Propagation and Quadratic Criterion (2006) (259)
- Vicinal Risk Minimization (2000) (256)
- Semi-Supervised Learning (Adaptive Computation and Machine Learning) (2006) (245)
- Large-scale validation and analysis of interleaved search evaluation (2012) (226)
- A General Boosting Method and its Application to Learning Ranking Functions for Web Search (2007) (216)
- Embedded Methods (2006) (206)
- Gradient descent optimization of smoothed information retrieval metrics (2010) (195)
- Kernel Dependency Estimation (2002) (185)
- A continuation method for semi-supervised SVMs (2006) (172)
- Approximation Methods for Gaussian Process Regression (2007) (169)
- An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models (2006) (147)
- Branch and Bound for Semi-Supervised Support Vector Machines (2006) (140)
- Modeling delayed feedback in display advertising (2014) (139)
- Measure Based Regularization (2003) (136)
- Early exit optimizations for additive machine learned ranking systems (2010) (133)
- Deterministic annealing for semi-supervised kernel machines (2006) (132)
- Learning to rank with (a lot of) word features (2010) (128)
- Intent-based diversification of web search results: metrics and algorithms (2011) (121)
- Model Selection for Small Sample Regression (2002) (116)
- The Greedy Miser: Learning under Test-time Budgets (2012) (114)
- Feature selection and transduction for prediction of molecular bioactivity for drug design (2003) (110)
- Multi-task learning for boosting with application to web search ranking (2010) (110)
- Deterministic Annealing for Multiple-Instance Learning (2007) (106)
- Supervised semantic indexing (2009) (101)
- An Analysis of Inference with the Universum (2007) (97)
- Web spam identification through content and hyperlinks (2008) (91)
- Active Learning for Ranking through Expected Loss Optimization (2010) (90)
- Field-aware Factorization Machines in a Real-world Online Advertising System (2017) (89)
- Classifier cascades and trees for minimizing feature evaluation cost (2014) (86)
- Learning to suggest: a machine learning framework for ranking query suggestions (2012) (83)
- Boosted multi-task learning (2010) (82)
- Future directions in learning to rank (2010) (79)
- Transductive Inference for Estimating Values of Functions (1999) (78)
- Large Margin Taxonomy Embedding for Document Categorization (2008) (75)
- Classifier Cascade for Minimizing Feature Evaluation Cost (2012) (72)
- Tighter Bounds for Structured Estimation (2008) (72)
- Multi-class Feature Selection with Support Vector Machines (2007) (69)
- Implicit Surface Modelling with a Globally Regularised Basis of Compact Support (2006) (67)
- Object categorization with SVM: kernels for local features (2004) (67)
- Graph regularization methods for Web spam detection (2010) (66)
- Large margin optimization of ranking measures (2007) (61)
- Scaling Learning Algorithms toward AI (2007) (59)
- Second order optimization of kernel parameters (2008) (58)
- A Machine Learning Approach to Conjoint Analysis (2004) (57)
- Active Learning for Parzen Window Classifier (2005) (52)
- Distance Metric Learning for Kernel Machines (2012) (52)
- Semi-Supervised Text Classification Using EM (2006) (51)
- Feature Selection for Support Vector Machines Using Genetic Algorithms (2004) (51)
- Global ranking by exploiting user clicks (2009) (48)
- Large-Scale Learning with String Kernels (2007) (48)
- Improved Preconditioner for Hessian Free Optimization (2011) (41)
- Learning more powerful test statistics for click-based retrieval evaluation (2010) (37)
- Incorporating Invariances in Non-Linear Support Vector Machines (2001) (37)
- Estimating Predictive Variances with Kernel Ridge Regression (2005) (32)
- Incorporating invariances in nonlinear Support Vector Machines (2001) (31)
- Bounds on error expectation for SVM (2000) (31)
- Large margin taxonomy embedding with an application to document categorization (2008) (30)
- Implicit surface modelling as an eigenvalue problem (2005) (29)
- Large-Scale Kernel Machines (Neural Information Processing) (2007) (28)
- Probabilistic Semi-Supervised Clustering with Constraints (2006) (27)
- A Discussion of Semi-Supervised Learning and Transduction (2006) (27)
- An Augmented PAC Model for Semi-Supervised Learning (2006) (26)
- Offline Evaluation of Response Prediction in Online Advertising Auctions (2015) (23)
- An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron (2005) (20)
- Support Vector Machines for Image Classification (1998) (17)
- Combining a Filter Method with SVMs (2006) (17)
- Large-Scale Algorithms (2006) (15)
- Learning with Transformation Invariant Kernels (2007) (15)
- Open Problem: Regret Bounds for Thompson Sampling (2012) (14)
- Data-Dependent Regularization (2006) (13)
- KDD Cup 2001 data analysis: prediction of molecular bioactivity for drug Design-Binding to Thrombin (2001) (13)
- Deterministic Annealing for Semi-Supervised Structured Output Learning (2012) (13)
- Large-Scale Parallel SVM Implementation (2007) (13)
- Cost-sensitive Learning for Utility Optimization in Online Advertising Auctions (2016) (13)
- Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge (2002) (13)
- Beyond binary relevance: preferences, diversity, and set-level judgments (2008) (13)
- Biological Sequence Design using Batched Bayesian Optimization (2019) (12)
- Gaussian Processes and the Null-Category Noise Model (2006) (12)
- Estimating the Leave-One-Out Error for Classification Learning with SVMs (2001) (10)
- A taxonomy of semi-supervised learning algorithms (2005) (10)
- Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions (2006) (10)
- Semi-Supervised Learning in Practice (2006) (9)
- Support Vector Machines : principes d'induction, Réglage automatique et connaissances à priori (2004) (8)
- Adaptive Parameters for Entity Recognition with Perceptron HMMs (2010) (7)
- Semi-Supervised Learning through Principal Directions Estimation (2003) (7)
- The Improved Fast Gauss Transform with Applications to Machine Learning (2007) (7)
- A Distributed Sequential Solver for Large-Scale SVMs (2007) (6)
- A Test Collection of Preference Judgments (2017) (6)
- Support Vector Machines et Classification d ’ Images (1998) (5)
- Analysis of Benchmarks (2006) (4)
- Metric-Based Approaches for Semi-Supervised Regression and Classification (2006) (4)
- Spectral Methods for Dimensionality Reduction (2006) (3)
- Graph-Based Methods (2006) (3)
- A Comparison of Generative Models for Sequence Design (2020) (3)
- Cross-Validation Optimization for Structured Hessian Kernel Methods (2006) (3)
- Some thoughts about Gaussian Processes (2005) (3)
- Transductive Inference and Semi-Supervised Learning (2006) (3)
- A Taxonomy for Semi-Supervised Learning Methods (2006) (2)
- Change of Representation (2006) (2)
- Building SVMs with Reduced Classifier Complexity (2007) (2)
- Data cleaning algorithms with applications to micro-array experiments (2001) (2)
- Risks of Semi-Supervised Learning: How Unlabeled Data Can Degrade Performance of Generative Classifiers (2006) (2)
- Training Invariant SVMs Using Selective Sampling (2007) (1)
- Brisk Kernel Independent Component Analysis (2007) (1)
- Semi-Supervised Learning Using Semi-Definite Programming (2006) (1)
- Learning to Rank Challenge Future directions in learning to rank (2011) (1)
- Newton Methods for Fast Semisupervised Linear SVMs (2007) (1)
- Fast Kernel Learning with Sparse Inverted Index (2007) (1)
- Semi-supervised classification with hyperlinks (2007) (1)
- The Geometric Basis of Semi-Supervised Learning (2006) (0)
- Semi-Supervised Learning with Conditional Harmonic Mixing (2006) (0)
- Notation and Symbols (2006) (0)
- No . TR-165 Learning with Transformation Invariant Kernels † (2007) (0)
- Low-Density Separation (2006) (0)
- Transductive Support Vector Machines (2006) (0)
- Chapter 20 Combining a Filter Method with SVMs (0)
- No . YR-2008-002 MULTI-CLASS FEATURE SELECTION WITH SUPPORT VECTOR MACHINES (2008) (0)
- Support Vector Machines Et Classiication D' Images Support Vector Machines for Image Classiication (1998) (0)
- Graph Kernels by Spectral Transforms (2006) (0)
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