The Organization and Visualization of Document Corpora: A Probabilistic Approach. - Mark A. Girolami; Alexei Vinokourov; Ata Kabán (DEXA Workshop, 2000)

Initialized and Guided EM-Clustering of Sparse Binary Data with Application to Text Based Documents. - Ata Kabán; Mark A. Girolami (ICPR, 2000)

Finding Topics in Dynamical Text: Application to Chat Line Discussions. - Ella Bingham; Ata Kabán; Mark A. Girolami (WWW Posters, 2001)

Sign-changing filters similar to cells in primary visual cortex emerge by independent component analysis of temporally convolved natural image sequences. - András Lörincz; Botond Szatmáry; Ata Kabán (Neurocomputing, 2001)

A Combined Latent Class and Trait Model for the Analysis and Visualization of Discrete Data. - Ata Kabán; Mark A. Girolami (IEEE Trans. Pattern Anal. Mach. Intell., 2001)

A General Framework for a Principled Hierarchical Visualization of Multivariate Data. - Ata Kabán; Peter Tiño; Mark A. Girolami (IDEAL, 2002)

A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams. - Ata Kabán; Mark A. Girolami (J. Intell. Inf. Syst., 2002)

Fast Extraction of Semantic Features from a Latent Semantic Indexed Text Corpus. - Ata Kabán; Mark A. Girolami (Neural Process. Lett., 2002)

An Adaptive Novelty Detection Approach to Low Level Analysis of Images Corrupted by Mixed Noise. - Alexander N. Dolia; Martin Lages; Ata Kabán (KES, 2003)

Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles. - Mark A. Girolami; Ata Kabán (NIPS, 2003)

On an equivalence between PLSI and LDA. - Mark A. Girolami; Ata Kabán (SIGIR, 2003)

Topic Identification in Dynamical Text by Complexity Pursuit. - Ella Bingham; Ata Kabán; Mark A. Girolami (Neural Process. Lett., 2003)

Context based identification of user communities from Internet chat. - Ata Kabán; Xin Wang 006 (IJCNN, 2004)

A generative probabilistic approach to visualizing sets of symbolic sequences. - Peter Tiño; Ata Kabán; Yi Sun 001 (KDD, 2004)

Learning to Read Between the Lines: The Aspect Bernoulli Model. - Ata Kabán; Ella Bingham; T. Hirsimäki (SDM, 2004)

Finding Uninformative Features in Binary Data. - Xin Wang 006; Ata Kabán (IDEAL, 2005)

A variational Bayesian method for rectified factor analysis. - Markus Harva; Ata Kabán (IJCNN, 2005)

A Scalable Generative Topographic Mapping for Sparse Data Sequences. - Ata Kabán (ITCC (1), 2005)

Finding Young Stellar Populations in Elliptical Galaxies from Independent Components of Optical Spectra. - Ata Kabán; Louisa Nolan; Somak Raychaudhury (SDM, 2005)

Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains. - Mark A. Girolami; Ata Kabán (Data Min. Knowl. Discov., 2005)

Semisupervised Learning of Hierarchical Latent Trait Models for Data Visualization. - Ian T. Nabney; Yi Sun 001; Peter Tiño; Ata Kabán (IEEE Trans. Knowl. Data Eng., 2005)

On Class Visualisation for High Dimensional Data: Exploring Scientific Data Sets. - Ata Kabán; Jianyong Sun; Somak Raychaudhury; Louisa Nolan (Discovery Science, 2006)

Model-Based Estimation of Word Saliency in Text. - Xin Wang 006; Ata Kabán (Discovery Science, 2006)

Deconvolutive Clustering of Markov States. - Ata Kabán; Xin Wang 006 (ECML, 2006)

ICA-Based Binary Feature Construction. - Ata Kabán; Ella Bingham (ICA, 2006)

State Aggregation in Higher Order Markov Chains for Finding Online Communities. - Xin Wang 006; Ata Kabán (IDEAL, 2006)

Robust mixtures in the presence of measurement errors. - Jianyong Sun; Ata Kabán; Somak Raychaudhury (ICML, 2007)

Robust Visual Mining of Data with Error Information. - Jianyong Sun; Ata Kabán; Somak Raychaudhury (PKDD, 2007)

Predictive Modelling of Heterogeneous Sequence Collections by Topographic Ordering of Histories. - Ata Kabán (Mach. Learn., 2007)

On Bayesian classification with Laplace priors. - Ata Kabán (Pattern Recognit. Lett., 2007)

Variational learning for rectified factor analysis. - Markus Harva; Ata Kabán (Signal Process., 2007)

A Probabilistic Neighbourhood Translation Approach for Non-standard Text Categorisation. - Ata Kabán (Discovery Science, 2008)

Learning with Lq<1 vs L1-Norm Regularisation with Exponentially Many Irrelevant Features. - Ata Kabán; Robert J. Durrant (ECML/PKDD (1), 2008)

A dynamic bibliometric model for identifying online communities. - Xin Wang 006; Ata Kabán (Data Min. Knowl. Discov., 2008)

Factorisation and denoising of 0-1 data: A variational approach. - Ata Kabán; Ella Bingham (Neurocomputing, 2008)

When is 'nearest neighbour' meaningful: A converse theorem and implications. - Robert J. Durrant; Ata Kabán (J. Complex., 2009)

The aspect Bernoulli model: multiple causes of presences and absences. - Ella Bingham; Ata Kabán; Mikael Fortelius (Pattern Anal. Appl., 2009)

A Bound on the Performance of LDA in Randomly Projected Data Spaces. - Robert J. Durrant; Ata Kabán (ICPR, 2010)

Robust mixture modeling using the Pearson type VII distribution. - Jianyong Sun; Ata Kabán; Jonathan M. Garibaldi (IJCNN, 2010)

Compressed fisher linear discriminant analysis: classification of randomly projected data. - Robert J. Durrant; Ata Kabán (KDD, 2010)

Robust mixture clustering using Pearson type VII distribution. - Jianyong Sun; Ata Kabán; Jonathan M. Garibaldi (Pattern Recognit. Lett., 2010)

A fast algorithm for robust mixtures in the presence of measurement errors. - Jianyong Sun; Ata Kabán (IEEE Trans. Neural Networks, 2010)

Multi-class classification in the presence of labelling errors. - Jakramate Bootkrajang; Ata Kabán (ESANN, 2011)

On the distance concentration awareness of certain data reduction techniques. - Ata Kabán (Pattern Recognit., 2011)

On extending quantum behaved particle swarm optimization to multiobjective context. - Heyam H. Al-Baity; Souham Meshoul; Ata Kabán (IEEE Congress on Evolutionary Computation, 2012)

Constrained Multi-objective Optimization Using a Quantum Behaved Particle Swarm. - Heyam H. Al-Baity; Souham Meshoul; Ata Kabán (ICONIP (3), 2012)

Multi-task signal recovery by higher level hyper-parameter sharing. - Sakinah Ali Pitchay; Ata Kabán (ICPR, 2012)

Single-frame Signal Recovery using a Similarity-prior based on Pearson Type VII MRF. - Sakinah Ali Pitchay; Ata Kabán (ICPRAM (1), 2012)

Label-Noise Robust Logistic Regression and Its Applications. - Jakramate Bootkrajang; Ata Kabán (ECML/PKDD (1), 2012)

Single-frame image recovery using a Pearson type VII MRF. - Ata Kabán; Sakinah Ali Pitchay (Neurocomputing, 2012)

Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space. - Robert J. Durrant; Ata Kabán (AISTATS, 2012)

A tight bound on the performance of Fisher's linear discriminant in randomly projected data spaces. - Robert John Durrant; Ata Kabán (Pattern Recognit. Lett., 2012)

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

Random Projections as Regularizers: Learning a Linear Discriminant Ensemble from Fewer Observations than Dimensions. - Robert J. Durrant; Ata Kabán (ACML, 2013)

Dimension-Adaptive Bounds on Compressive FLD Classification. - Ata Kabán; Robert J. Durrant (ALT, 2013)

Towards large scale continuous EDA: a random matrix theory perspective. - Ata Kabán; Jakramate Bootkrajang; Robert John Durrant (GECCO, 2013)

A New Look at Compressed Ordinary Least Squares. - Ata Kabán (ICDM Workshops, 2013)

Sharp Generalization Error Bounds for Randomly-projected Classifiers. - Robert J. Durrant; Ata Kabán (ICML (3), 2013)

Learning a Label-Noise Robust Logistic Regression: Analysis and Experiments. - Jakramate Bootkrajang; Ata Kabán (IDEAL, 2013)

Estimation of the Regularisation Parameter in Huber-MRF for Image Resolution Enhancement. - Sakinah Ali Pitchay; Ata Kabán (IDEAL, 2013)

Boosting in the presence of label noise. - Jakramate Bootkrajang; Ata Kabán (UAI, 2013)

K-Nearest-Neighbours with a novel similarity measure for intrusion detection. - Zhenghui Ma; Ata Kabán (UKCI, 2013)

Random projections versus random selection of features for classification of high dimensional data. - Sachin Mylavarapu; Ata Kabán (UKCI, 2013)

Classification of mislabelled microarrays using robust sparse logistic regression. - Jakramate Bootkrajang; Ata Kabán (Bioinform., 2013)

Fractional Norm Regularization: Learning With Very Few Relevant Features. - Ata Kabán (IEEE Trans. Neural Networks Learn. Syst., 2013)

New Bounds on Compressive Linear Least Squares Regression. - Ata Kabán (AISTATS, 2014)

A comprehensive introduction to label noise. - Benoît Frénay; Ata Kabán (ESANN, 2014)

Two approaches of using heavy tails in high dimensional EDA. - Momodou L. Sanyang; Hanno Muehlbrandt; Ata Kabán (ICDM Workshops, 2014)

Multivariate Cauchy EDA Optimisation. - Momodou L. Sanyang; Ata Kabán (IDEAL, 2014)

Quantum behaved particle swarm optimization for data clustering with multiple objectives. - Heyam H. Al-Baity; Souham Meshoul; Ata Kabán; Lilac A. E. Al-Safadi (SoCPaR, 2014)

Learning kernel logistic regression in the presence of class label noise. - Jakramate Bootkrajang; Ata Kabán (Pattern Recognit., 2014)

Non-asymptotic Analysis of Compressive Fisher Discriminants in terms of the Effective Dimension. - Ata Kabán (ACML, 2015)

A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections. - Ata Kabán (ACML, 2015)

Heavy tails with parameter adaptation in random projection based continuous EDA. - Momodou L. Sanyang; Ata Kabán (CEC, 2015)

Improved Bounds on the Dot Product under Random Projection and Random Sign Projection. - Ata Kabán (KDD, 2015)

Special issue on advances in learning with label noise. - Benoît Frénay; Ata Kabán (Neurocomputing, 2015)

Random projections as regularizers: learning a linear discriminant from fewer observations than dimensions. - Robert J. Durrant; Ata Kabán (Mach. Learn., 2015)

Finding Small Sets of Random Fourier Features for Shift-Invariant Kernel Approximation. - Frank-Michael Schleif; Ata Kabán; Peter Tiño (ANNPR, 2016)

How effective is Cauchy-EDA in high dimensions? - Momodou L. Sanyang; Robert J. Durrant; Ata Kabán (CEC, 2016)

Large scale continuous EDA using mutual information. - Qi Xu; Momodou L. Sanyang; Ata Kabán (CEC, 2016)

REMEDA: Random Embedding EDA for Optimising Functions with Intrinsic Dimension. - Momodou L. Sanyang; Ata Kabán (PPSN, 2016)

Toward Large-Scale Continuous EDA: A Random Matrix Theory Perspective. - Ata Kabán; Jakramate Bootkrajang; Robert J. Durrant (Evol. Comput., 2016)

On Compressive Ensemble Induced Regularisation: How Close is the Finite Ensemble Precision Matrix to the Infinite Ensemble? - Ata Kabán (ALT, 2017)

Joint blind source separation and declipping: A geometric approach for time disjoint sources. - Alastair Turl; Ata Kabán (ISSPIT, 2017)

Tighter Guarantees for the Compressive Multi-layer Perceptron. - Ata Kabán; Yamonporn Thummanusarn (TPNC, 2018)

Data Dependent Dissimilarity Measures (NII Shonan Meeting 2018-13). - Kai Ming Ting; Takashi Washio; Ata Kabán (NII Shonan Meet. Rep., 2018)

Dimension-Free Error Bounds from Random Projections. - Ata Kabán (AAAI, 2019)

Exploiting geometric structure in mixture proportion estimation with generalised Blanchard-Lee-Scott estimators. - Henry W. J. Reeve; Ata Kabán (ALT, 2019)

Classification with unknown class-conditional label noise on non-compact feature spaces. - Henry W. J. Reeve; Ata Kabán (COLT, 2019)

Experiments with Random Projections Ensembles: Linear Versus Quadratic Discriminants. - Xi Zhang; Ata Kabán (ICDM Workshops, 2019)

Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise. - Henry W. J. Reeve; Ata Kabán (ICML, 2019)

Compressive Learning of Multi-layer Perceptrons: An Error Analysis. - Ata Kabán (IJCNN, 2019)

Large-Scale Estimation of Distribution Algorithms with Adaptive Heavy Tailed Random Projection Ensembles. - Momodou L. Sanyang; Ata Kabán (J. Comput. Sci. Technol., 2019)

Optimistic Bounds for Multi-output Learning. - Henry W. J. Reeve; Ata Kabán (ICML, 2020)

Optimistic bounds for multi-output prediction. - Henry W. J. Reeve; Ata Kabán (CoRR, 2020)

Structure from Randomness in Halfspace Learning with the Zero-One Loss. - Ata Kabán; Robert J. Durrant (J. Artif. Intell. Res., 2020)

Random Projection Through the Lens of Data Complexity Indicators. - Yamonporn Thummanusarn; Ata Kabán (ICDM (Workshops), 2021)

Statistical optimality conditions for compressive ensembles. - Henry W. J. Reeve; Ata Kabán (CoRR, 2021)

Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles. - Zhanliang Huang; Yunwen Lei; Ata Kabán (ECML/PKDD (4), 2022)

Approximability and Generalisation. - Andrew James Turner; Ata Kabán (CoRR, 2022)

Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms. - Sijia Zhou; Yunwen Lei; Ata Kabán (NeurIPS, 2023)

The Effect of Intrinsic Dimension on Metric Learning under Compression. - Efstratios Palias; Ata Kabán (CoRR, 2023)

PAC-learning with approximate predictors. - Andrew James Turner; Ata Kabán (Mach. Learn., 2023)

Optimization and Learning With Randomly Compressed Gradient Updates. - Zhanliang Huang; Yunwen Lei; Ata Kabán (Neural Comput., 2023)

The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification. - Efstratios Palias; Ata Kabán (Stat. Comput., 2023)

Data Complexity via Random Projection. - Yamonporn Thummanusarn; Ata Kabán (ICDM (Workshops), 2024)

Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension. - Efstratios Palias; Ata Kabán (IJCNN, 2024)

Self-certified Tuple-Wise Deep Learning. - Sijia Zhou; Yunwen Lei; Ata Kabán (ECML/PKDD (2), 2024)

Heterogeneous sets in dimensionality reduction and ensemble learning. - Henry W. J. Reeve; Ata Kabán; Jakramate Bootkrajang (Mach. Learn., 2024)

Structure discovery in PAC-learning by random projections. - Ata Kabán; Henry W. J. Reeve (Mach. Learn., 2024)

Efficient learning with projected histograms. - Zhanliang Huang; Ata Kabán; Henry W. J. Reeve (Data Min. Knowl. Discov., 2024)

Learning to Sample in Stochastic Optimization. - Sijia Zhou; Yunwen Lei; Ata Kabán (UAI, 2025)

Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis. - Sijia Zhou; Yunwen Lei; Ata Kabán (CoRR, 2025)