Ata Kabán

Orcid: 0000-0003-3733-7064

Affiliations:
  • University of Birmingham, School of Computer Science, UK


According to our database1, Ata Kabán authored at least 108 papers between 2000 and 2024.

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

Timeline

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Bibliography

2024
Efficient learning with projected histograms.
Data Min. Knowl. Discov., November, 2024

Structure discovery in PAC-learning by random projections.
Mach. Learn., July, 2024

Heterogeneous sets in dimensionality reduction and ensemble learning.
Mach. Learn., April, 2024

Self-certified Tuple-Wise Deep Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension.
Proceedings of the International Joint Conference on Neural Networks, 2024

2023
The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification.
Stat. Comput., August, 2023

Optimization and Learning With Randomly Compressed Gradient Updates.
Neural Comput., July, 2023

PAC-learning with approximate predictors.
Mach. Learn., May, 2023

The Effect of Intrinsic Dimension on Metric Learning under Compression.
CoRR, 2023

Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Approximability and Generalisation.
CoRR, 2022

Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021
Statistical optimality conditions for compressive ensembles.
CoRR, 2021

Random Projection Through the Lens of Data Complexity Indicators.
Proceedings of the 2021 International Conference on Data Mining, 2021

2020
Structure from Randomness in Halfspace Learning with the Zero-One Loss.
J. Artif. Intell. Res., 2020

Optimistic bounds for multi-output prediction.
CoRR, 2020

Optimistic Bounds for Multi-output Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Large-Scale Estimation of Distribution Algorithms with Adaptive Heavy Tailed Random Projection Ensembles.
J. Comput. Sci. Technol., 2019

Compressive Learning of Multi-layer Perceptrons: An Error Analysis.
Proceedings of the International Joint Conference on Neural Networks, 2019

Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise.
Proceedings of the 36th International Conference on Machine Learning, 2019

Experiments with Random Projections Ensembles: Linear Versus Quadratic Discriminants.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Classification with unknown class-conditional label noise on non-compact feature spaces.
Proceedings of the Conference on Learning Theory, 2019

Exploiting geometric structure in mixture proportion estimation with generalised Blanchard-Lee-Scott estimators.
Proceedings of the Algorithmic Learning Theory, 2019

Dimension-Free Error Bounds from Random Projections.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Data Dependent Dissimilarity Measures (NII Shonan Meeting 2018-13).
NII Shonan Meet. Rep., 2018

Tighter Guarantees for the Compressive Multi-layer Perceptron.
Proceedings of the Theory and Practice of Natural Computing - 7th International Conference, 2018

2017
Joint blind source separation and declipping: A geometric approach for time disjoint sources.
Proceedings of the 2017 IEEE International Symposium on Signal Processing and Information Technology, 2017

On Compressive Ensemble Induced Regularisation: How Close is the Finite Ensemble Precision Matrix to the Infinite Ensemble?
Proceedings of the International Conference on Algorithmic Learning Theory, 2017

2016
Toward Large-Scale Continuous EDA: A Random Matrix Theory Perspective.
Evol. Comput., 2016

REMEDA: Random Embedding EDA for Optimising Functions with Intrinsic Dimension.
Proceedings of the Parallel Problem Solving from Nature - PPSN XIV, 2016

Large scale continuous EDA using mutual information.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

How effective is Cauchy-EDA in high dimensions?
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

Finding Small Sets of Random Fourier Features for Shift-Invariant Kernel Approximation.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2016

2015
Random projections as regularizers: learning a linear discriminant from fewer observations than dimensions.
Mach. Learn., 2015

Special issue on advances in learning with label noise.
Neurocomputing, 2015

Improved Bounds on the Dot Product under Random Projection and Random Sign Projection.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Heavy tails with parameter adaptation in random projection based continuous EDA.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections.
Proceedings of The 7th Asian Conference on Machine Learning, 2015

Non-asymptotic Analysis of Compressive Fisher Discriminants in terms of the Effective Dimension.
Proceedings of The 7th Asian Conference on Machine Learning, 2015

2014
Learning kernel logistic regression in the presence of class label noise.
Pattern Recognit., 2014

Quantum behaved particle swarm optimization for data clustering with multiple objectives.
Proceedings of the 6th International Conference of Soft Computing and Pattern Recognition, 2014

Multivariate Cauchy EDA Optimisation.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2014, 2014

Two approaches of using heavy tails in high dimensional EDA.
Proceedings of the 2014 IEEE International Conference on Data Mining Workshops, 2014

A comprehensive introduction to label noise.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

New Bounds on Compressive Linear Least Squares Regression.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Fractional Norm Regularization: Learning With Very Few Relevant Features.
IEEE Trans. Neural Networks Learn. Syst., 2013

Classification of mislabelled microarrays using robust sparse logistic regression.
Bioinform., 2013

Random projections versus random selection of features for classification of high dimensional data.
Proceedings of the 13th UK Workshop on Computational Intelligence, 2013

K-Nearest-Neighbours with a novel similarity measure for intrusion detection.
Proceedings of the 13th UK Workshop on Computational Intelligence, 2013

Boosting in the presence of label noise.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Estimation of the Regularisation Parameter in Huber-MRF for Image Resolution Enhancement.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2013, 2013

Learning a Label-Noise Robust Logistic Regression: Analysis and Experiments.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2013, 2013

Sharp Generalization Error Bounds for Randomly-projected Classifiers.
Proceedings of the 30th International Conference on Machine Learning, 2013

A New Look at Compressed Ordinary Least Squares.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Towards large scale continuous EDA: a random matrix theory perspective.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Dimension-Adaptive Bounds on Compressive FLD Classification.
Proceedings of the Algorithmic Learning Theory - 24th International Conference, 2013

Random Projections as Regularizers: Learning a Linear Discriminant Ensemble from Fewer Observations than Dimensions.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
Non-parametric detection of meaningless distances in high dimensional data.
Stat. Comput., 2012

A tight bound on the performance of Fisher's linear discriminant in randomly projected data spaces.
Pattern Recognit. Lett., 2012

Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Single-frame image recovery using a Pearson type VII MRF.
Neurocomputing, 2012

Label-Noise Robust Logistic Regression and Its Applications.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Single-frame Signal Recovery using a Similarity-prior based on Pearson Type VII MRF.
Proceedings of the ICPRAM 2012, 2012

Multi-task signal recovery by higher level hyper-parameter sharing.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

Constrained Multi-objective Optimization Using a Quantum Behaved Particle Swarm.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

On extending quantum behaved particle swarm optimization to multiobjective context.
Proceedings of the IEEE Congress on Evolutionary Computation, 2012

2011
On the distance concentration awareness of certain data reduction techniques.
Pattern Recognit., 2011

Multi-class classification in the presence of labelling errors.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

2010
A fast algorithm for robust mixtures in the presence of measurement errors.
IEEE Trans. Neural Networks, 2010

Robust mixture clustering using Pearson type VII distribution.
Pattern Recognit. Lett., 2010

Compressed fisher linear discriminant analysis: classification of randomly projected data.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

Robust mixture modeling using the Pearson type VII distribution.
Proceedings of the International Joint Conference on Neural Networks, 2010

A Bound on the Performance of LDA in Randomly Projected Data Spaces.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

2009
The aspect Bernoulli model: multiple causes of presences and absences.
Pattern Anal. Appl., 2009

When is 'nearest neighbour' meaningful: A converse theorem and implications.
J. Complex., 2009

2008
Factorisation and denoising of 0-1 data: A variational approach.
Neurocomputing, 2008

A dynamic bibliometric model for identifying online communities.
Data Min. Knowl. Discov., 2008

Learning with L<sub>q<1</sub> vs L<sub>1</sub>-Norm Regularisation with Exponentially Many Irrelevant Features.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

A Probabilistic Neighbourhood Translation Approach for Non-standard Text Categorisation.
Proceedings of the Discovery Science, 11th International Conference, 2008

2007
Variational learning for rectified factor analysis.
Signal Process., 2007

On Bayesian classification with Laplace priors.
Pattern Recognit. Lett., 2007

Predictive Modelling of Heterogeneous Sequence Collections by Topographic Ordering of Histories.
Mach. Learn., 2007

Robust Visual Mining of Data with Error Information.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Robust mixtures in the presence of measurement errors.
Proceedings of the Machine Learning, 2007

2006
State Aggregation in Higher Order Markov Chains for Finding Online Communities.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2006

ICA-Based Binary Feature Construction.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

Deconvolutive Clustering of Markov States.
Proceedings of the Machine Learning: ECML 2006, 2006

Model-Based Estimation of Word Saliency in Text.
Proceedings of the Discovery Science, 9th International Conference, 2006

On Class Visualisation for High Dimensional Data: Exploring Scientific Data Sets.
Proceedings of the Discovery Science, 9th International Conference, 2006

2005
Semisupervised Learning of Hierarchical Latent Trait Models for Data Visualization.
IEEE Trans. Knowl. Data Eng., 2005

Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains.
Data Min. Knowl. Discov., 2005

Finding Young Stellar Populations in Elliptical Galaxies from Independent Components of Optical Spectra.
Proceedings of the 2005 SIAM International Conference on Data Mining, 2005

A Scalable Generative Topographic Mapping for Sparse Data Sequences.
Proceedings of the International Symposium on Information Technology: Coding and Computing (ITCC 2005), 2005

Finding Uninformative Features in Binary Data.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2005

2004
Learning to Read Between the Lines: The Aspect Bernoulli Model.
Proceedings of the Fourth SIAM International Conference on Data Mining, 2004

A generative probabilistic approach to visualizing sets of symbolic sequences.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

2003
Topic Identification in Dynamical Text by Complexity Pursuit.
Neural Process. Lett., 2003

On an equivalence between PLSI and LDA.
Proceedings of the SIGIR 2003: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, July 28, 2003

Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

An Adaptive Novelty Detection Approach to Low Level Analysis of Images Corrupted by Mixed Noise.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2003

2002
Fast Extraction of Semantic Features from a Latent Semantic Indexed Text Corpus.
Neural Process. Lett., 2002

A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams.
J. Intell. Inf. Syst., 2002

A General Framework for a Principled Hierarchical Visualization of Multivariate Data.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2002

2001
A Combined Latent Class and Trait Model for the Analysis and Visualization of Discrete Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2001

Sign-changing filters similar to cells in primary visual cortex emerge by independent component analysis of temporally convolved natural image sequences.
Neurocomputing, 2001

Finding Topics in Dynamical Text: Application to Chat Line Discussions.
Proceedings of the Poster Proceedings of the Tenth International World Wide Web Conference, 2001

2000
Initialized and Guided EM-Clustering of Sparse Binary Data with Application to Text Based Documents.
Proceedings of the 15th International Conference on Pattern Recognition, 2000

The Organization and Visualization of Document Corpora: A Probabilistic Approach.
Proceedings of the 11th International Workshop on Database and Expert Systems Applications (DEXA'00), 2000


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