Balázs Kégl

According to our database1, Balázs Kégl authored at least 57 papers between 1998 and 2018.

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

Timeline

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PhD thesis 
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Bibliography

2018
Similarity encoding for learning with dirty categorical variables.
Machine Learning, 2018

Spurious samples in deep generative models: bug or feature?
CoRR, 2018

Similarity encoding for learning with dirty categorical variables.
CoRR, 2018

2017
Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy.
CoRR, 2017

Out-of-Class Novelty Generation : An Experimental Foundation.
Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence, 2017

2016
Digits that are not: Generating new types through deep neural nets.
CoRR, 2016

Digits that are not: Generating new types through deep neural nets.
Proceedings of the Seventh International Conference on Computational Creativity, UPMC, Paris, France, June 27, 2016

How machine learning won the Higgs boson challenge.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2014
The Higgs boson machine learning challenge.
Proceedings of the Workshop on High-energy Physics and Machine Learning, 2014

Open Problem: A (missing) boosting-type convergence result for AdaBoost.MH with factorized multi-class classifiers.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Tune and mix: learning to rank using ensembles of calibrated multi-class classifiers.
Machine Learning, 2013

Correlation-based construction of neighborhood and edge features.
CoRR, 2013

The return of AdaBoost.MH: multi-class Hamming trees.
CoRR, 2013

Gossip-based distributed stochastic bandit algorithms.
Proceedings of the 30th International Conference on Machine Learning, 2013

Collaborative hyperparameter tuning.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
MULTIBOOST: A Multi-purpose Boosting Package.
Journal of Machine Learning Research, 2012

Adaptive Metropolis with Online Relabeling.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Fast classification using sparse decision DAGs.
Proceedings of the 29th International Conference on Machine Learning, 2012

Peer-to-Peer Multi-class Boosting.
Proceedings of the Euro-Par 2012 Parallel Processing - 18th International Conference, 2012

2011
Ranking by calibrated AdaBoost.
Proceedings of the Yahoo! Learning to Rank Challenge, 2011

A Robust Ranking Methodology Based on Diverse Calibration of AdaBoost.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Algorithms for Hyper-Parameter Optimization.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Contributions to machine learning: the unsupervised, the supervised, and the Bayesian.
, 2011

2010
Invariant pattern recognition using contourlets and AdaBoost.
Pattern Recognition, 2010

Multi-objective Reinforcement Learning for Responsive Grids.
J. Grid Comput., 2010

Palmprint Classification Using Wavelets and AdaBoost.
Proceedings of the Advances in Neural Networks, 2010

Fast boosting using adversarial bandits.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Surrogating the surrogate: accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009
Accelerating AdaBoost using UCB.
Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009, 2009

A One-Class Classification Approach for Protein Sequences and Structures.
Proceedings of the Bioinformatics Research and Applications, 5th International Symposium, 2009

Boosting products of base classifiers.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Utility-Based Reinforcement Learning for Reactive Grids.
Proceedings of the 2008 International Conference on Autonomic Computing, 2008

Grid Differentiated Services: A Reinforcement Learning Approach.
Proceedings of the 8th IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2008), 2008

2007
Image denoising with complex ridgelets.
Pattern Recognition, 2007

Privacy-preserving boosting.
Data Min. Knowl. Discov., 2007

Feature extraction using Radon, wavelet and fourier transform.
Proceedings of the IEEE International Conference on Systems, 2007

Palmprint classification using contourlets.
Proceedings of the IEEE International Conference on Systems, 2007

Learning the 2-D Topology of Images.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Aggregate features and ADABOOSTfor music classification.
Machine Learning, 2006

Invariant Radon-Wavelet Packet Signatures for Pattern Recognition.
Proceedings of the Canadian Conference on Electrical and Computer Engineering, 2006

2005
Frame-Level Audio Feature Extraction Using AdaBoost.
Proceedings of the ISMIR 2005, 2005

Geometry in sound: a speech/Music audio Classifier Inspired by an Image Classifier.
Proceedings of the 2005 International Computer Music Conference, 2005

2004
Boosting on Manifolds: Adaptive Regularization of Base Classifiers.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Generalization Error and Algorithmic Convergence of Median Boosting.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Robust Regression by Boosting the Median.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
Piecewise Linear Skeletonization Using Principal Curves.
IEEE Trans. Pattern Anal. Mach. Intell., 2002

Data-dependent margin-based generalization bounds for classification.
Journal of Machine Learning Research, 2002

Intrinsic Dimension Estimation Using Packing Numbers.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Combining and Adapting Software Quality Predictive Models by Genetic Algorithms.
Proceedings of the 17th IEEE International Conference on Automated Software Engineering (ASE 2002), 2002

Combining Software Quality Predictive Models: An Evolutionary Approach.
Proceedings of the 18th International Conference on Software Maintenance (ICSM 2002), 2002

2001
Non-parametric identification of dynamic non-linear systems by a Hermite Series Approach.
Int. J. Systems Science, 2001

Data-Dependent Margin-Based Generalization Bounds for Classification.
Proceedings of the Computational Learning Theory, 2001

2000
Learning and Design of Principal Curves.
IEEE Trans. Pattern Anal. Mach. Intell., 2000

Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification.
Proceedings of the 15th International Conference on Pattern Recognition, 2000

Piecewise Linear Skeletonization Using Principal Curves.
Proceedings of the 15th International Conference on Pattern Recognition, 2000

1998
A Polygonal Line Algorithm for Constructing Principal Curves.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Radial basis function networks in nonparametric classification and function learning.
Proceedings of the Fourteenth International Conference on Pattern Recognition, 1998


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