| 2009 |
|---|
| 88 | EE | Richard Nock,
Brice Magdalou,
Nicolas Sanz,
Eric Briys,
Fred Celimene,
Frank Nielsen:
Information geometries and Microeconomic Theories
CoRR abs/0901.2586: (2009) |
| 87 | EE | Frank Nielsen,
Richard Nock:
Hyperbolic Voronoi diagrams made easy
CoRR abs/0903.3287: (2009) |
| 86 | EE | Richard Nock,
Pascal Vaillant,
Claudia Henry,
Frank Nielsen:
Soft memberships for spectral clustering, with application to permeable language distinction.
Pattern Recognition 42(1): 43-53 (2009) |
| 2008 |
|---|
| 85 | EE | Richard Nock,
Panu Luosto,
Jyrki Kivinen:
Mixed Bregman Clustering with Approximation Guarantees.
ECML/PKDD (2) 2008: 154-169 |
| 84 | EE | Frank Nielsen,
Richard Nock:
Clustering Multivariate Normal Distributions.
ETVC 2008: 164-174 |
| 83 | EE | Richard Nock,
Frank Nielsen:
Intrinsic Geometries in Learning.
ETVC 2008: 175-215 |
| 82 | EE | Frank Nielsen,
Richard Nock:
Bregman sided and symmetrized centroids.
ICPR 2008: 1-4 |
| 81 | EE | Richard Nock,
Frank Nielsen:
On the efficient minimization of convex surrogates in supervised learning.
ICPR 2008: 1-4 |
| 80 | EE | Richard Nock,
Frank Nielsen:
On the Efficient Minimization of Classification Calibrated Surrogates.
NIPS 2008: 1201-1208 |
| 79 | EE | Richard Nock,
Nicolas Sanz,
Fred Celimene,
Frank Nielsen:
Staring at Economic Aggregators through Information Lenses
CoRR abs/0801.0390: (2008) |
| 78 | EE | Pascal Vaillant,
Richard Nock,
Claudia Henry:
Analyse spectrale des textes: détection automatique des frontières de langue et de discours
CoRR abs/0810.1212: (2008) |
| 77 | EE | Richard Nock,
Pascal Vaillant,
Frank Nielsen,
Claudia Henry:
Soft Uncoupling of Markov Chains for Permeable Language Distinction: A New Algorithm
CoRR abs/0810.1261: (2008) |
| 76 | EE | Frank Nielsen,
Richard Nock:
On the smallest enclosing information disk.
Inf. Process. Lett. 105(3): 93-97 (2008) |
| 2007 |
|---|
| 75 | EE | Claudia Henry,
Richard Nock,
Frank Nielsen:
Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree.
IJCAI 2007: 842-847 |
| 74 | EE | Frank Nielsen,
Richard Nock:
Fast Graph Segmentation Based on Statistical Aggregation Phenomena.
MVA 2007: 150-153 |
| 73 | EE | Frank Nielsen,
Jean-Daniel Boissonnat,
Richard Nock:
On Bregman Voronoi diagrams.
SODA 2007: 746-755 |
| 72 | EE | Frank Nielsen,
Jean-Daniel Boissonnat,
Richard Nock:
Visualizing bregman voronoi diagrams.
Symposium on Computational Geometry 2007: 121-122 |
| 71 | EE | Richard Nock,
Frank Nielsen:
A Real generalization of discrete AdaBoost.
Artif. Intell. 171(1): 25-41 (2007) |
| 70 | EE | Frank Nielsen,
Jean-Daniel Boissonnat,
Richard Nock:
Bregman Voronoi Diagrams: Properties, Algorithms and Applications
CoRR abs/0709.2196: (2007) |
| 69 | EE | Frank Nielsen,
Richard Nock:
On the Centroids of Symmetrized Bregman Divergences
CoRR abs/0711.3242: (2007) |
| 68 | EE | Pierre-Alain Laur,
Jean-Emile Symphor,
Richard Nock,
Pascal Poncelet:
Statistical supports for mining sequential patterns and improving the incremental update process on data streams.
Intell. Data Anal. 11(1): 29-47 (2007) |
| 67 | EE | Pierre-Alain Laur,
Richard Nock,
Jean-Emile Symphor,
Pascal Poncelet:
Mining evolving data streams for frequent patterns.
Pattern Recognition 40(2): 492-503 (2007) |
| 66 | EE | Richard Nock,
Frank Nielsen:
Self-improved gaps almost everywhere for the agnostic approximation of monomials.
Theor. Comput. Sci. 377(1-3): 139-150 (2007) |
| 2006 |
|---|
| 65 | EE | Frank Nielsen,
Richard Nock:
On the Smallest Enclosing Information Disk.
CCCG 2006 |
| 64 | EE | Svetlana Kiritchenko,
Stan Matwin,
Richard Nock,
A. Fazel Famili:
Learning and Evaluation in the Presence of Class Hierarchies: Application to Text Categorization.
Canadian Conference on AI 2006: 395-406 |
| 63 | | Richard Nock,
Frank Nielsen:
A Real Generalization of Discrete AdaBoost.
ECAI 2006: 509-515 |
| 62 | | Richard Nock,
Pascal Vaillant,
Frank Nielsen,
Claudia Henry:
Soft Uncoupling of Markov Chains for Permeable Language Distinction: A New Algorithm.
ECAI 2006: 823-824 |
| 61 | EE | Richard Nock,
Pierre-Alain Laur,
Jean-Emile Symphor:
Statistical Borders for Incremental Mining.
ICPR (3) 2006: 212-215 |
| 60 | EE | Patrice Lefaucheur,
Richard Nock:
Robust Multiclass Ensemble Classifiers via Symmetric Functions.
ICPR (4) 2006: 136-139 |
| 59 | EE | Frank Nielsen,
Richard Nock:
On approximating the smallest enclosing Bregman Balls.
Symposium on Computational Geometry 2006: 485-486 |
| 58 | EE | Richard Nock,
Frank Nielsen:
On Weighting Clustering.
IEEE Trans. Pattern Anal. Mach. Intell. 28(8): 1223-1235 (2006) |
| 2005 |
|---|
| 57 | EE | Frank Nielsen,
Richard Nock:
ClickRemoval: interactive pinpoint image object removal.
ACM Multimedia 2005: 315-318 |
| 56 | EE | Pierre-Alain Laur,
Richard Nock,
Jean-Emile Symphor,
Pascal Poncelet:
On the estimation of frequent itemsets for data streams: theory and experiments.
CIKM 2005: 327-328 |
| 55 | EE | Frank Nielsen,
Richard Nock:
Interactive Pinpoint Image Object Removal.
CVPR (2) 2005: 1191 |
| 54 | EE | Richard Nock,
Frank Nielsen:
Fitting the Smallest Enclosing Bregman Ball.
ECML 2005: 649-656 |
| 53 | EE | Frank Nielsen,
Richard Nock:
Interactive Point-and-Click Segmentation for Object Removal in Digital Images.
ICCV-HCI 2005: 131-140 |
| 52 | EE | Pierre-Alain Laur,
Jean-Emile Symphor,
Richard Nock,
Pascal Poncelet:
Statistical Supports for Frequent Itemsets on Data Streams.
MLDM 2005: 395-404 |
| 51 | EE | Richard Nock,
Babak Esfandiari:
On-Line Adaptive Filtering of Web Pages.
PKDD 2005: 634-642 |
| 50 | EE | Babak Esfandiari,
Richard Nock:
Adaptive filtering of advertisements on web pages.
WWW (Special interest tracks and posters) 2005: 916-917 |
| 49 | EE | Frank Nielsen,
Richard Nock:
A fast deterministic smallest enclosing disk approximation algorithm.
Inf. Process. Lett. 93(6): 263-268 (2005) |
| 48 | EE | Richard Nock,
Frank Nielsen:
Semi-supervised statistical region refinement for color image segmentation.
Pattern Recognition 38(6): 835-846 (2005) |
| 47 | EE | Jean-Christophe Janodet,
Richard Nock,
Marc Sebban,
Henri-Maxime Suchier:
Adaptation du boosting à l'inférence grammaticale via l'utilisation d'un oracle de confiance.
Revue d'Intelligence Artificielle 19(4-5): 713-740 (2005) |
| 2004 |
|---|
| 46 | EE | Frank Nielsen,
Richard Nock:
Approximating smallest enclosing disks.
CCCG 2004: 124-127 |
| 45 | EE | Richard Nock,
Frank Nielsen:
Grouping with Bias Revisited.
CVPR (2) 2004: 460-465 |
| 44 | EE | Frank Nielsen,
Richard Nock:
Approximating Smallest Enclosing Balls.
ICCSA (3) 2004: 147-157 |
| 43 | EE | Jean-Christophe Janodet,
Richard Nock,
Marc Sebban,
Henri-Maxime Suchier:
Boosting grammatical inference with confidence oracles.
ICML 2004 |
| 42 | EE | Richard Nock,
Vincent Pagé:
Grouping with Bias for Distribution-Free Mixture Model Estimation.
ICPR (2) 2004: 44-47 |
| 41 | EE | Richard Nock,
Frank Nielsen:
Improving Clustering Algorithms through Constrained Convex Optimization.
ICPR (4) 2004: 557-560 |
| 40 | EE | Richard Nock,
Frank Nielsen:
An Abstract Weighting Framework for Clustering Algorithms.
SDM 2004 |
| 39 | EE | Richard Nock,
Frank Nielsen:
Statistical Region Merging.
IEEE Trans. Pattern Anal. Mach. Intell. 26(11): 1452-1458 (2004) |
| 38 | EE | Richard Nock,
Frank Nielsen:
On domain-partitioning induction criteria: worst-case bounds for the worst-case based.
Theor. Comput. Sci. 321(2-3): 371-382 (2004) |
| 2003 |
|---|
| 37 | EE | Frank Nielsen,
Richard Nock:
On Region Merging: The Statistical Soundness of Fast Sorting, with Applications.
CVPR (2) 2003: 19-26 |
| 36 | EE | Richard Nock,
Marc Sebban,
Didier Bernard:
A Simple Locally Adaptive Nearest Neighbor Rule With Application To Pollution Forecasting.
IJPRAI 17(8): 1369-1382 (2003) |
| 35 | EE | Richard Nock,
Tapio Elomaa,
Matti Kääriäinen:
Reduced Error Pruning of branching programs cannot be approximated to within a logarithmic factor.
Inf. Process. Lett. 87(2): 73-78 (2003) |
| 34 | EE | Richard Nock:
Complexity in the case against accuracy estimation.
Theor. Comput. Sci. 1-3(301): 143-165 (2003) |
| 2002 |
|---|
| 33 | EE | Richard Nock,
Patrice Lefaucheur:
A Robust Boosting Algorithm.
ECML 2002: 319-330 |
| 32 | EE | Richard Nock:
Inducing Interpretable Voting Classifiers without Trading Accuracy for Simplicity: Theoretical Results, Approximation Algorithms, and Experiments.
J. Artif. Intell. Res. (JAIR) 17: 137-170 (2002) |
| 31 | EE | Marc Sebban,
Richard Nock,
Stéphane Lallich:
Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem.
Journal of Machine Learning Research 3: 863-885 (2002) |
| 30 | EE | Marc Sebban,
Richard Nock:
A hybrid filter/wrapper approach of feature selection using information theory.
Pattern Recognition 35(4): 835-846 (2002) |
| 2001 |
|---|
| 29 | EE | Richard Nock:
Fast and Reliable Color Region Merging inspired by Decision Tree Pruning.
CVPR (1) 2001: 271- |
| 28 | | Marc Sebban,
Richard Nock:
Improvement of Nearest-Neighbor Classifiers via Support Vector Machines.
FLAIRS Conference 2001: 113-117 |
| 27 | | Marc Sebban,
Richard Nock,
Stéphane Lallich:
Boosting Neighborhood-Based Classifiers.
ICML 2001: 505-512 |
| 26 | | Richard Nock,
Marc Sebban:
Advances in Adaptive Prototype Weighting and Selection.
International Journal on Artificial Intelligence Tools 10(1-2): 137-155 (2001) |
| 25 | | Richard Nock,
Marc Sebban:
An improved bound on the finite-sample risk of the nearest neighbor rule.
Pattern Recognition Letters 22(3/4): 407-412 (2001) |
| 24 | | Richard Nock,
Marc Sebban:
A Bayesian boosting theorem.
Pattern Recognition Letters 22(3/4): 413-419 (2001) |
| 2000 |
|---|
| 23 | EE | Richard Nock,
Marc Sebban:
Sharper Bounds for the Hardness of Prototype and Feature Selection.
ALT 2000: 224-237 |
| 22 | EE | Christophe Fiorio,
Richard Nock:
A Concentration-Based Adaptive Approach to Region Merging of Optimal Time and Space Complexities.
BMVC 2000 |
| 21 | EE | Marc Sebban,
Richard Nock:
Identifying and Eliminating Irrelevant Instances Using Information Theory.
Canadian Conference on AI 2000: 90-101 |
| 20 | EE | Richard Nock,
Marc Sebban,
Pascal Jabby:
A Symmetric Nearest Neighbor Learning Rule.
EWCBR 2000: 222-233 |
| 19 | | Richard Nock,
Marc Sebban:
A Boosting-Based Prototype Weighting and Selection Scheme.
FLAIRS Conference 2000: 71-75 |
| 18 | | Christophe Fiorio,
Richard Nock:
Sorted Region Merging to Maximize Test Reliability.
ICIP 2000 |
| 17 | | Marc Sebban,
Richard Nock:
Instance Pruning as an Information Preserving Problem.
ICML 2000: 855-862 |
| 16 | EE | Marc Sebban,
Richard Nock:
Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery.
PKDD 2000: 44-53 |
| 15 | EE | Marc Sebban,
Richard Nock:
Combining Feature and Example Pruning by Uncertainty Minimization.
UAI 2000: 533-540 |
| 14 | EE | Marc Sebban,
Richard Nock,
Jean-Hugues Chauchat,
Ricco Rakotomalala:
Impact of learning set quality and size on decision tree performances.
Int. J. Comput. Syst. Signal 1(1): 85-105 (2000) |
| 1999 |
|---|
| 13 | EE | Richard Nock:
Complexity in the Case against Accuracy: When Building one Function-Free Horn Clause is as Hard as Any.
ATL 1999: 182-193 |
| 12 | EE | Richard Nock,
Pascal Jappy:
A ``Top-Down and Prune'' Induction Scheme for Constrained Decision Committees.
IDA 1999: 27-38 |
| 11 | | Marc Sebban,
Richard Nock:
Contribution of Boosting in Wrapper Models.
PKDD 1999: 214-222 |
| 10 | | Richard Nock,
Marc Sebban,
Pascal Jappy:
Experiments on a Representation-Independent "Top-Down and Prune" Induction Scheme.
PKDD 1999: 223-231 |
| 9 | EE | Richard Nock,
Pascal Jappy:
Decision tree based induction of decision lists.
Intell. Data Anal. 3(3): 227-240 (1999) |
| 1998 |
|---|
| 8 | | Richard Nock,
Babak Esfandiari:
Oracles and Assistants: Machine Learning Applied to Network Supervision.
Canadian Conference on AI 1998: 86-98 |
| 7 | EE | Pascal Jappy,
Richard Nock:
PAC Learning Conceptual Graphs.
ICCS 1998: 303-318 |
| 6 | | Richard Nock,
Pascal Jappy:
On the Power of Decision Lists.
ICML 1998: 413-420 |
| 5 | | Richard Nock,
Pascal Jappy:
Function-Free Horn Clauses Are Hard to Approximate.
ILP 1998: 195-204 |
| 4 | EE | Richard Nock,
Pascal Jappy,
Jean Sallantin:
Generalized Graph Colorability and Compressibility of Boolean Formulae.
ISAAC 1998: 237-246 |
| 3 | | Olivier Gascuel,
Bernadette Bouchon-Meunier,
Gilles Caraux,
Patrick Gallinari,
Alain Guénoche,
Yann Guermeur,
Yves Lechevallier,
Christophe Marsala,
Laurent Miclet,
Jacques Nicolas,
Richard Nock,
Mohammed Ramdani,
Michèle Sebag,
Basavanneppa Tallur,
Gilles Venturini,
Patrick Vitte:
Twelve Numerical, Symbolic and Hybrid Supervised Classification Methods.
IJPRAI 12(4): 517-571 (1998) |
| 1996 |
|---|
| 2 | | Pascal Jappy,
Richard Nock,
Olivier Gascuel:
Negative Robust Learning Results from Horn Claus Programs.
ICML 1996: 258-265 |
| 1995 |
|---|
| 1 | | Richard Nock,
Olivier Gascuel:
On Learning Decision Committees.
ICML 1995: 413-420 |
