Richard Nock

According to our database1, Richard Nock authored at least 178 papers between 1995 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2019
Proper-Composite Loss Functions in Arbitrary Dimensions.
CoRR, 2019

Adversarial Networks and Autoencoders: The Primal-Dual Relationship and Generalization Bounds.
CoRR, 2019

New Tricks for Estimating Gradients of Expectations.
CoRR, 2019

Non-Euclidean Embeddings for Graph Analytics and Visualisation.
Proceedings of the SIGGRAPH Asia 2019 Posters, 2019

Lossless or Quantized Boosting with Integer Arithmetic.
Proceedings of the 36th International Conference on Machine Learning, 2019

Monge blunts Bayes: Hardness Results for Adversarial Training.
Proceedings of the 36th International Conference on Machine Learning, 2019

Min-Max Statistical Alignment for Transfer Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
The Bregman chord divergence.
CoRR, 2018

Lipschitz Networks and Distributional Robustness.
CoRR, 2018

Hyperparameter Learning for Conditional Mean Embeddings with Rademacher Complexity Bounds.
CoRR, 2018

D-PAGE: Diverse Paraphrase Generation.
CoRR, 2018

Private Text Classification.
CoRR, 2018

Integral Privacy for Density Estimation with Approximation Guarantees.
CoRR, 2018

Monge beats Bayes: Hardness Results for Adversarial Training.
CoRR, 2018

Boosted Density Estimation Remastered.
CoRR, 2018

Entity Resolution and Federated Learning get a Federated Resolution.
CoRR, 2018

Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Representation Learning of Compositional Data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Variational Network Inference: Strong and Stable with Concrete Support.
Proceedings of the 35th International Conference on Machine Learning, 2018

On the Geometry of Mixtures of Prescribed Distributions.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
Generalizing Skew Jensen Divergences and Bregman Divergences With Comparative Convexity.
IEEE Signal Process. Lett., 2017

MaxEnt Upper Bounds for the Differential Entropy of Univariate Continuous Distributions.
IEEE Signal Process. Lett., 2017

Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption.
CoRR, 2017

On w-mixtures: Finite convex combinations of prescribed component distributions.
CoRR, 2017

Distribution-free Evolvability of Vector Spaces: All it takes is a Generating Set.
CoRR, 2017

f-GANs in an Information Geometric Nutshell.
CoRR, 2017

Generalizing Jensen and Bregman divergences with comparative convexity and the statistical Bhattacharyya distances with comparable means.
CoRR, 2017

Semi-parametric Network Structure Discovery Models.
CoRR, 2017

Bregman Divergences from Comparative Convexity.
Proceedings of the Geometric Science of Information - Third International Conference, 2017

Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
On Conformal Divergences and Their Population Minimizers.
IEEE Trans. Information Theory, 2016

Making Neural Networks Robust to Label Noise: a Loss Correction Approach.
CoRR, 2016

Loss factorization, weakly supervised learning and label noise robustness.
CoRR, 2016

Fast Learning from Distributed Datasets without Entity Matching.
CoRR, 2016

The Crossover Process: Learnability meets Protection from Inference Attacks.
CoRR, 2016

A scaled Bregman theorem with applications.
CoRR, 2016

k-variates++: more pluses in the k-means++.
CoRR, 2016

A series of maximum entropy upper bounds of the differential entropy.
CoRR, 2016

Fast $(1+ε)$-approximation of the Löwner extremal matrices of high-dimensional symmetric matrices.
CoRR, 2016

Large Margin Nearest Neighbor Classification using Curved Mahalanobis Distances.
CoRR, 2016

Tsallis Regularized Optimal Transport and Ecological Inference.
CoRR, 2016

Patch Matching with Polynomial Exponential Families and Projective Divergences.
Proceedings of the Similarity Search and Applications - 9th International Conference, 2016

On Regularizing Rademacher Observation Losses.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Classification with mixtures of curved mahalanobis metrics.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

2015
Gentle Nearest Neighbors Boosting over Proper Scoring Rules.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Structural knowledge learning from maps for supervised land cover/use classification: Application to the monitoring of land cover/use maps in French Guiana.
Computers & Geosciences, 2015

Rademacher Observations, Private Data, and Boosting.
CoRR, 2015

Learning Games and Rademacher Observations Losses.
CoRR, 2015

Total Jensen divergences: Definition, properties and clustering.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014
Optimal Interval Clustering: Application to Bregman Clustering and Statistical Mixture Learning.
IEEE Signal Process. Lett., 2014

On the Chi Square and Higher-Order Chi Distances for Approximating $f$ -Divergences.
IEEE Signal Process. Lett., 2014

On Clustering Histograms with k-Means by Using Mixed α-Divergences.
Entropy, 2014

Further results on the hyperbolic Voronoi diagrams.
CoRR, 2014

Further heuristics for $k$-means: The merge-and-split heuristic and the $(k, l)$-means.
CoRR, 2014

A note on the optimal scalar Bregman k-means clustering with an application to learning best statistical mixtures.
CoRR, 2014

(Almost) No Label No Cry.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Boosting Stochastic Newton with Entropy Constraint for Large-Scale Image Classification.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Visualizing hyperbolic Voronoi diagrams.
Proceedings of the 30th Annual Symposium on Computational Geometry, 2014

2013
Boosting k-Nearest Neighbors Classification.
Proceedings of the Advanced Topics in Computer Vision, 2013

Combining Feature and Prototype Pruning by Uncertainty Minimization
CoRR, 2013

Total Jensen divergences: Definition, Properties and k-Means++ Clustering.
CoRR, 2013

Information-geometric lenses for multiple foci+contexts interfaces.
Proceedings of the SIGGRAPH Asia 2013, 2013

Non-linear book manifolds: learning from associations the dynamic geometry of digital libraries.
Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries, 2013

Demonstrator of a Tourist Recommendation System.
Proceedings of the Big Data Analytics - Second International Conference, 2013

Consensus Region Merging for Image Segmentation.
Proceedings of the 2nd IAPR Asian Conference on Pattern Recognition, 2013

2012
Leveraging k-NN for generic classification boosting.
Neurocomputing, 2012

Boosting k-NN for Categorization of Natural Scenes.
International Journal of Computer Vision, 2012

The hyperbolic Voronoi diagram in arbitrary dimension
CoRR, 2012

Boosting Nearest Neighbors for the Efficient Estimation of Posteriors.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Biomedical Images Classification by Universal Nearest Neighbours Classifier Using Posterior Probability.
Proceedings of the Machine Learning in Medical Imaging - Third International Workshop, 2012

Classification of biological cells using bio-inspired descriptors.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

2011
Skew Jensen-Bregman Voronoi Diagrams.
Trans. Computational Science, 2011

Income distributions and decomposable divergence measures.
J. Economic Theory, 2011

A closed-form expression for the Sharma-Mittal entropy of exponential families
CoRR, 2011

Inducing Interpretable Voting Classifiers without Trading Accuracy for Simplicity: Theoretical Results, Approximation Algorithms
CoRR, 2011

On Rényi and Tsallis entropies and divergences for exponential families
CoRR, 2011

On tracking portfolios with certainty equivalents on a generalization of Markowitz model: the Fool, the Wise and the Adaptive.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Bregman Voronoi Diagrams.
Discrete & Computational Geometry, 2010

Boosting k-NN for categorization of natural scenes
CoRR, 2010

K-NN boosting prototype learning for object classification.
Proceedings of the 11th International Workshop on Image Analysis for Multimedia Interactive Services, 2010

Jensen-Bregman Voronoi Diagrams and Centroidal Tessellations.
Proceedings of the Seventh International Symposium on Voronoi Diagrams in Science and Engineering, 2010

Boosting Bayesian MAP Classification.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

Entropies and cross-entropies of exponential families.
Proceedings of the International Conference on Image Processing, 2010

Hierarchical Gaussian Mixture Model.
Proceedings of the IEEE International Conference on Acoustics, 2010

Multi-class Leveraged κ-NN for Image Classification.
Proceedings of the Computer Vision - ACCV 2010, 2010

2009
Sided and symmetrized Bregman centroids.
IEEE Trans. Information Theory, 2009

Soft memberships for spectral clustering, with application to permeable language distinction.
Pattern Recognition, 2009

Bregman Divergences and Surrogates for Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Approximating Smallest Enclosing Balls with Applications to Machine Learning.
Int. J. Comput. Geometry Appl., 2009

Hyperbolic Voronoi diagrams made easy
CoRR, 2009

Information geometries and Microeconomic Theories
CoRR, 2009

The Dual Voronoi Diagrams with Respect to Representational Bregman Divergences.
Proceedings of the Sixth International Symposium on Voronoi Diagrams, 2009

Simplifying Gaussian mixture models via entropic quantization.
Proceedings of the 17th European Signal Processing Conference, 2009

Levels of Details for Gaussian Mixture Models.
Proceedings of the Computer Vision, 2009

2008
On the smallest enclosing information disk.
Inf. Process. Lett., 2008

Soft Uncoupling of Markov Chains for Permeable Language Distinction: A New Algorithm
CoRR, 2008

Analyse spectrale des textes: détection automatique des frontières de langue et de discours
CoRR, 2008

Staring at Economic Aggregators through Information Lenses
CoRR, 2008

Mixed Bregman Clustering with Approximation Guarantees.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

On the Efficient Minimization of Classification Calibrated Surrogates.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Quantum Voronoi diagrams and Holevo channel capacity for 1-qubit quantum states.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008

On the efficient minimization of convex surrogates in supervised learning.
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Bregman sided and symmetrized centroids.
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Intrinsic Geometries in Learning.
Proceedings of the Emerging Trends in Visual Computing, 2008

Clustering Multivariate Normal Distributions.
Proceedings of the Emerging Trends in Visual Computing, 2008

2007
Self-improved gaps almost everywhere for the agnostic approximation of monomials.
Theor. Comput. Sci., 2007

Mining evolving data streams for frequent patterns.
Pattern Recognition, 2007

Statistical supports for mining sequential patterns and improving the incremental update process on data streams.
Intell. Data Anal., 2007

On the Centroids of Symmetrized Bregman Divergences
CoRR, 2007

Bregman Voronoi Diagrams: Properties, Algorithms and Applications
CoRR, 2007

A Real generalization of discrete AdaBoost.
Artif. Intell., 2007

On Bregman Voronoi diagrams.
Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2007

Fast Graph Segmentation Based on Statistical Aggregation Phenomena.
Proceedings of the IAPR Conference on Machine Vision Applications (IAPR MVA 2007), 2007

Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree.
Proceedings of the IJCAI 2007, 2007

Visualizing bregman voronoi diagrams.
Proceedings of the 23rd ACM Symposium on Computational Geometry, Gyeongju, 2007

2006
On Weighting Clustering.
IEEE Trans. Pattern Anal. Mach. Intell., 2006

Statistical Borders for Incremental Mining.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Robust Multiclass Ensemble Classifiers via Symmetric Functions.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

On approximating the smallest enclosing Bregman Balls.
Proceedings of the 22nd ACM Symposium on Computational Geometry, 2006

Learning and Evaluation in the Presence of Class Hierarchies: Application to Text Categorization.
Proceedings of the Advances in Artificial Intelligence, 2006

2005
Adaptation du boosting à l'inférence grammaticale via l'utilisation d'un oracle de confiance.
Revue d'Intelligence Artificielle, 2005

Semi-supervised statistical region refinement for color image segmentation.
Pattern Recognition, 2005

A fast deterministic smallest enclosing disk approximation algorithm.
Inf. Process. Lett., 2005

Adaptive filtering of advertisements on web pages.
Proceedings of the 14th international conference on World Wide Web, 2005

On-Line Adaptive Filtering of Web Pages.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

ClickRemoval: interactive pinpoint image object removal.
Proceedings of the 13th ACM International Conference on Multimedia, 2005

Statistical Supports for Frequent Itemsets on Data Streams.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

Interactive Point-and-Click Segmentation for Object Removal in Digital Images.
Proceedings of the Computer Vision in Human-Computer Interaction, 2005

Fitting the Smallest Enclosing Bregman Ball.
Proceedings of the Machine Learning: ECML 2005, 2005

Interactive Pinpoint Image Object Removal.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

On the estimation of frequent itemsets for data streams: theory and experiments.
Proceedings of the 2005 ACM CIKM International Conference on Information and Knowledge Management, Bremen, Germany, October 31, 2005

2004
On domain-partitioning induction criteria: worst-case bounds for the worst-case based.
Theor. Comput. Sci., 2004

Statistical Region Merging.
IEEE Trans. Pattern Anal. Mach. Intell., 2004

An Abstract Weighting Framework for Clustering Algorithms.
Proceedings of the Fourth SIAM International Conference on Data Mining, 2004

Grouping with Bias for Distribution-Free Mixture Model Estimation.
Proceedings of the 17th International Conference on Pattern Recognition, 2004

Improving Clustering Algorithms through Constrained Convex Optimization.
Proceedings of the 17th International Conference on Pattern Recognition, 2004

Boosting grammatical inference with confidence oracles.
Proceedings of the Machine Learning, 2004

Approximating Smallest Enclosing Balls.
Proceedings of the Computational Science and Its Applications, 2004

Grouping with Bias Revisited.
Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2004), with CD-ROM, 27 June, 2004

Approximating smallest enclosing disks.
Proceedings of the 16th Canadian Conference on Computational Geometry, 2004

2003
Complexity in the case against accuracy estimation.
Theor. Comput. Sci., 2003

Reduced Error Pruning of branching programs cannot be approximated to within a logarithmic factor.
Inf. Process. Lett., 2003

A Simple Locally Adaptive Nearest Neighbor Rule With Application To Pollution Forecasting.
IJPRAI, 2003

On Region Merging: The Statistical Soundness of Fast Sorting, with Applications.
Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2003), 2003

2002
A hybrid filter/wrapper approach of feature selection using information theory.
Pattern Recognition, 2002

Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem.
J. Mach. Learn. Res., 2002

Inducing Interpretable Voting Classifiers without Trading Accuracy for Simplicity: Theoretical Results, Approximation Algorithms, and Experiments.
J. Artif. Intell. Res., 2002

A Robust Boosting Algorithm.
Proceedings of the Machine Learning: ECML 2002, 2002

2001
A Bayesian boosting theorem.
Pattern Recognition Letters, 2001

An improved bound on the finite-sample risk of the nearest neighbor rule.
Pattern Recognition Letters, 2001

Advances in Adaptive Prototype Weighting and Selection.
International Journal on Artificial Intelligence Tools, 2001

Boosting Neighborhood-Based Classifiers.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Improvement of Nearest-Neighbor Classifiers via Support Vector Machines.
Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference, 2001

Fast and Reliable Color Region Merging inspired by Decision Tree Pruning.
Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), 2001

2000
Impact of learning set quality and size on decision tree performances.
Int. J. Comput. Syst. Signal, 2000

Combining Feature and Example Pruning by Uncertainty Minimization.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2000

Instance Pruning as an Information Preserving Problem.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Sorted Region Merging to Maximize Test Reliability.
Proceedings of the 2000 International Conference on Image Processing, 2000

A Boosting-Based Prototype Weighting and Selection Scheme.
Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference, 2000

A Symmetric Nearest Neighbor Learning Rule.
Proceedings of the Advances in Case-Based Reasoning, 5th European Workshop, 2000

A Concentration-Based Adaptive Approach to Region Merging of Optimal Time and Space Complexities.
Proceedings of the British Machine Vision Conference 2000, 2000

Sharper Bounds for the Hardness of Prototype and Feature Selection.
Proceedings of the Algorithmic Learning Theory, 11th International Conference, 2000

Identifying and Eliminating Irrelevant Instances Using Information Theory.
Proceedings of the Advances in Artificial Intelligence, 2000

1999
Decision tree based induction of decision lists.
Intell. Data Anal., 1999

Contribution of Boosting in Wrapper Models.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 1999

Experiments on a Representation-Independent "Top-Down and Prune" Induction Scheme.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 1999

A "Top-Down and Prune" Induction Scheme for Constrained Decision Committees.
Proceedings of the Advances in Intelligent Data Analysis, Third International Symposium, 1999

Complexity in the Case against Accuracy: When Building one Function-Free Horn Clause is as Hard as Any.
Proceedings of the Algorithmic Learning Theory, 10th International Conference, 1999

1998
Twelve Numerical, Symbolic and Hybrid Supervised Classification Methods.
IJPRAI, 1998

Generalized Graph Colorability and Compressibility of Boolean Formulae.
Proceedings of the Algorithms and Computation, 9th International Symposium, 1998

Function-Free Horn Clauses Are Hard to Approximate.
Proceedings of the Inductive Logic Programming, 8th International Workshop, 1998

Image segmentation using a generic, fast and non-parametric approach.
Proceedings of the Tenth IEEE International Conference on Tools with Artificial Intelligence, 1998

On the Power of Decision Lists.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

PAC Learning Conceptual Graphs.
Proceedings of the Conceptual Structures: Theory, 1998

Oracles and Assistants: Machine Learning Applied to Network Supervision.
Proceedings of the Advances in Artificial Intelligence, 1998

1996
Negative Robust Learning Results from Horn Claus Programs.
Proceedings of the Machine Learning, 1996

1995
On Learning Decision Committees.
Proceedings of the Machine Learning, 1995


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