Ata Kabán - RankMe

118 papers A* 10A 9B 21C 9Journal 44Unranked 25

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Learning to Sample in Stochastic Optimization. UAI Sijia Zhou, Yunwen Lei, Ata Kabán
2025	J	`jnl`	PAC-Bayes Guarantees for Data-Adaptive Pairwise Learning. Entropy Sijia Zhou, Yunwen Lei, Ata Kabán
2025	J	`jnl`	Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis. CoRR Sijia Zhou, Yunwen Lei, Ata Kabán
2024	B	`conf`	Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension. IJCNN Efstratios Palias, Ata Kabán
2024	—	`conf`	Data Complexity via Random Projection. ICDM (Workshops) Yamonporn Thummanusarn, Ata Kabán
2024	J	`jnl`	Efficient learning with projected histograms. Data Min. Knowl. Discov. Zhanliang Huang, Ata Kabán, Henry W. J. Reeve
2024	J	`jnl`	Heterogeneous sets in dimensionality reduction and ensemble learning. Mach. Learn. Henry W. J. Reeve, Ata Kabán, Jakramate Bootkrajang
2024	—	`conf`	Self-certified Tuple-Wise Deep Learning. ECML/PKDD (2) Sijia Zhou, Yunwen Lei, Ata Kabán
2024	J	`jnl`	Structure discovery in PAC-learning by random projections. Mach. Learn. Ata Kabán, Henry W. J. Reeve
2023	J	`jnl`	Optimization and Learning With Randomly Compressed Gradient Updates. Neural Comput. Zhanliang Huang, Yunwen Lei, Ata Kabán
2023	J	`jnl`	PAC-learning with approximate predictors. Mach. Learn. Andrew James Turner, Ata Kabán
2023	J	`jnl`	The Effect of Intrinsic Dimension on Metric Learning under Compression. CoRR Efstratios Palias, Ata Kabán
2023	J	`jnl`	The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification. Stat. Comput. Efstratios Palias, Ata Kabán
2023	A*	`conf`	Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms. NeurIPS Sijia Zhou, Yunwen Lei, Ata Kabán
2022	J	`jnl`	Approximability and Generalisation. CoRR Andrew James Turner, Ata Kabán
2022	—	`conf`	Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles. ECML/PKDD (4) Zhanliang Huang, Yunwen Lei, Ata Kabán
2021	—	`conf`	Random Projection Through the Lens of Data Complexity Indicators. ICDM (Workshops) Yamonporn Thummanusarn, Ata Kabán
2021	J	`jnl`	Statistical optimality conditions for compressive ensembles. CoRR Henry W. J. Reeve, Ata Kabán
2020	A*	`conf`	Optimistic Bounds for Multi-output Learning. ICML Henry W. J. Reeve, Ata Kabán
2020	J	`jnl`	Optimistic bounds for multi-output prediction. CoRR Henry W. J. Reeve, Ata Kabán
2020	J	`jnl`	Structure from Randomness in Halfspace Learning with the Zero-One Loss. J. Artif. Intell. Res. Ata Kabán, Robert J. Durrant
2019	J	`jnl`	Classification with unknown class conditional label noise on non-compact feature spaces. CoRR Henry W. J. Reeve, Ata Kabán
2019	A*	`conf`	Classification with unknown class-conditional label noise on non-compact feature spaces. COLT Henry W. J. Reeve, Ata Kabán
2019	B	`conf`	Compressive Learning of Multi-layer Perceptrons: An Error Analysis. IJCNN Ata Kabán
2019	A*	`conf`	Dimension-Free Error Bounds from Random Projections. AAAI Ata Kabán
2019	—	`conf`	Experiments with Random Projections Ensembles: Linear Versus Quadratic Discriminants. ICDM Workshops Xi Zhang, Ata Kabán
2019	B	`conf`	Exploiting geometric structure in mixture proportion estimation with generalised Blanchard-Lee-Scott estimators. ALT Henry W. J. Reeve, Ata Kabán
2019	A*	`conf`	Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise. ICML Henry W. J. Reeve, Ata Kabán
2019	J	`jnl`	Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise. CoRR Henry W. J. Reeve, Ata Kabán
2019	J	`jnl`	Large-Scale Estimation of Distribution Algorithms with Adaptive Heavy Tailed Random Projection Ensembles. J. Comput. Sci. Technol. Momodou L. Sanyang, Ata Kabán
2018	J	`jnl`	Data Dependent Dissimilarity Measures (NII Shonan Meeting 2018-13). NII Shonan Meet. Rep. Kai Ming Ting, Takashi Washio, Ata Kabán
2018	—	`conf`	Tighter Guarantees for the Compressive Multi-layer Perceptron. TPNC Ata Kabán, Yamonporn Thummanusarn
2017	—	`conf`	Joint blind source separation and declipping: A geometric approach for time disjoint sources. ISSPIT Alastair Turl, Ata Kabán
2017	B	`conf`	On Compressive Ensemble Induced Regularisation: How Close is the Finite Ensemble Precision Matrix to the Infinite Ensemble? ALT Ata Kabán
2016	—	`conf`	Finding Small Sets of Random Fourier Features for Shift-Invariant Kernel Approximation. ANNPR Frank-Michael Schleif, Ata Kabán, Peter Tiño
2016	B	`conf`	How effective is Cauchy-EDA in high dimensions? CEC Momodou L. Sanyang, Robert J. Durrant, Ata Kabán
2016	B	`conf`	Large scale continuous EDA using mutual information. CEC Qi Xu, Momodou L. Sanyang, Ata Kabán
2016	A	`conf`	REMEDA: Random Embedding EDA for Optimising Functions with Intrinsic Dimension. PPSN Momodou L. Sanyang, Ata Kabán
2016	J	`jnl`	Toward Large-Scale Continuous EDA: A Random Matrix Theory Perspective. Evol. Comput. Ata Kabán, Jakramate Bootkrajang, Robert J. Durrant
2015	C	`conf`	A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections. ACML Ata Kabán
2015	B	`conf`	Heavy tails with parameter adaptation in random projection based continuous EDA. CEC Momodou L. Sanyang, Ata Kabán
2015	A*	`conf`	Improved Bounds on the Dot Product under Random Projection and Random Sign Projection. KDD Ata Kabán
2015	C	`conf`	Non-asymptotic Analysis of Compressive Fisher Discriminants in terms of the Effective Dimension. ACML Ata Kabán
2015	J	`jnl`	Random projections as regularizers: learning a linear discriminant from fewer observations than dimensions. Mach. Learn. Robert J. Durrant, Ata Kabán
2015	J	`jnl`	Special issue on advances in learning with label noise. Neurocomputing Benoît Frénay, Ata Kabán
2014	B	`conf`	A comprehensive introduction to label noise. ESANN Benoît Frénay, Ata Kabán
2014	J	`jnl`	Learning kernel logistic regression in the presence of class label noise. Pattern Recognit. Jakramate Bootkrajang, Ata Kabán
2014	C	`conf`	Multivariate Cauchy EDA Optimisation. IDEAL Momodou L. Sanyang, Ata Kabán
2014	A	`conf`	New Bounds on Compressive Linear Least Squares Regression. AISTATS Ata Kabán
2014	—	`conf`	Quantum behaved particle swarm optimization for data clustering with multiple objectives. SoCPaR Heyam H. Al-Baity, Souham Meshoul, Ata Kabán, Lilac A. E. Al-Safadi
2014	—	`conf`	Two approaches of using heavy tails in high dimensional EDA. ICDM Workshops Momodou L. Sanyang, Hanno Muehlbrandt, Ata Kabán
2013	—	`conf`	A New Look at Compressed Ordinary Least Squares. ICDM Workshops Ata Kabán
2013	A	`conf`	Boosting in the presence of label noise. UAI Jakramate Bootkrajang, Ata Kabán
2013	J	`jnl`	Boosting in the presence of label noise. CoRR Jakramate Bootkrajang, Ata Kabán
2013	J	`jnl`	Classification of mislabelled microarrays using robust sparse logistic regression. Bioinform. Jakramate Bootkrajang, Ata Kabán
2013	B	`conf`	Dimension-Adaptive Bounds on Compressive FLD Classification. ALT Ata Kabán, Robert J. Durrant
2013	C	`conf`	Estimation of the Regularisation Parameter in Huber-MRF for Image Resolution Enhancement. IDEAL Sakinah Ali Pitchay, Ata Kabán
2013	J	`jnl`	Fractional Norm Regularization: Learning With Very Few Relevant Features. IEEE Trans. Neural Networks Learn. Syst. Ata Kabán
2013	—	`conf`	K-Nearest-Neighbours with a novel similarity measure for intrusion detection. UKCI Zhenghui Ma, Ata Kabán
2013	C	`conf`	Learning a Label-Noise Robust Logistic Regression: Analysis and Experiments. IDEAL Jakramate Bootkrajang, Ata Kabán
2013	C	`conf`	Random Projections as Regularizers: Learning a Linear Discriminant Ensemble from Fewer Observations than Dimensions. ACML Robert J. Durrant, Ata Kabán
2013	—	`conf`	Random projections versus random selection of features for classification of high dimensional data. UKCI Sachin Mylavarapu, Ata Kabán
2013	—	`conf`	Sharp Generalization Error Bounds for Randomly-projected Classifiers. ICML (3) Robert J. Durrant, Ata Kabán
2013	A	`conf`	Towards large scale continuous EDA: a random matrix theory perspective. GECCO Ata Kabán, Jakramate Bootkrajang, Robert John Durrant
2012	J	`jnl`	A tight bound on the performance of Fisher's linear discriminant in randomly projected data spaces. Pattern Recognit. Lett. Robert John Durrant, Ata Kabán
2012	—	`conf`	Constrained Multi-objective Optimization Using a Quantum Behaved Particle Swarm. ICONIP (3) Heyam H. Al-Baity, Souham Meshoul, Ata Kabán
2012	A	`conf`	Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space. AISTATS Robert J. Durrant, Ata Kabán
2012	—	`conf`	Label-Noise Robust Logistic Regression and Its Applications. ECML/PKDD (1) Jakramate Bootkrajang, Ata Kabán
2012	B	`conf`	Multi-task signal recovery by higher level hyper-parameter sharing. ICPR Sakinah Ali Pitchay, Ata Kabán
2012	J	`jnl`	Non-parametric detection of meaningless distances in high dimensional data. Stat. Comput. Ata Kabán
2012	B	`conf`	On extending quantum behaved particle swarm optimization to multiobjective context. IEEE Congress on Evolutionary Computation Heyam H. Al-Baity, Souham Meshoul, Ata Kabán
2012	—	`conf`	Single-frame Signal Recovery using a Similarity-prior based on Pearson Type VII MRF. ICPRAM (1) Sakinah Ali Pitchay, Ata Kabán
2012	J	`jnl`	Single-frame image recovery using a Pearson type VII MRF. Neurocomputing Ata Kabán, Sakinah Ali Pitchay
2011	B	`conf`	Multi-class classification in the presence of labelling errors. ESANN Jakramate Bootkrajang, Ata Kabán
2011	J	`jnl`	On the distance concentration awareness of certain data reduction techniques. Pattern Recognit. Ata Kabán
2010	B	`conf`	A Bound on the Performance of LDA in Randomly Projected Data Spaces. ICPR Robert J. Durrant, Ata Kabán
2010	J	`jnl`	A fast algorithm for robust mixtures in the presence of measurement errors. IEEE Trans. Neural Networks Jianyong Sun, Ata Kabán
2010	A*	`conf`	Compressed fisher linear discriminant analysis: classification of randomly projected data. KDD Robert J. Durrant, Ata Kabán
2010	J	`jnl`	Robust mixture clustering using Pearson type VII distribution. Pattern Recognit. Lett. Jianyong Sun, Ata Kabán, Jonathan M. Garibaldi
2010	B	`conf`	Robust mixture modeling using the Pearson type VII distribution. IJCNN Jianyong Sun, Ata Kabán, Jonathan M. Garibaldi
2009	J	`jnl`	The aspect Bernoulli model: multiple causes of presences and absences. Pattern Anal. Appl. Ella Bingham, Ata Kabán, Mikael Fortelius
2009	J	`jnl`	When is 'nearest neighbour' meaningful: A converse theorem and implications. J. Complex. Robert J. Durrant, Ata Kabán
2008	B	`conf`	A Probabilistic Neighbourhood Translation Approach for Non-standard Text Categorisation. Discovery Science Ata Kabán
2008	J	`jnl`	A dynamic bibliometric model for identifying online communities. Data Min. Knowl. Discov. Xin Wang, Ata Kabán
2008	J	`jnl`	Factorisation and denoising of 0-1 data: A variational approach. Neurocomputing Ata Kabán, Ella Bingham
2008	—	`conf`	Learning with L ECML/PKDD (1) Ata Kabán, Robert J. Durrant
2007	J	`jnl`	On Bayesian classification with Laplace priors. Pattern Recognit. Lett. Ata Kabán
2007	J	`jnl`	Predictive Modelling of Heterogeneous Sequence Collections by Topographic Ordering of Histories. Mach. Learn. Ata Kabán
2007	—	`conf`	Robust Visual Mining of Data with Error Information. PKDD Jianyong Sun, Ata Kabán, Somak Raychaudhury
2007	A*	`conf`	Robust mixtures in the presence of measurement errors. ICML Jianyong Sun, Ata Kabán, Somak Raychaudhury
2007	J	`jnl`	Variational learning for rectified factor analysis. Signal Process. Markus Harva, Ata Kabán
2006	—	`conf`	Deconvolutive Clustering of Markov States. ECML Ata Kabán, Xin Wang
2006	—	`conf`	ICA-Based Binary Feature Construction. ICA Ata Kabán, Ella Bingham
2006	B	`conf`	Model-Based Estimation of Word Saliency in Text. Discovery Science Xin Wang, Ata Kabán
2006	B	`conf`	On Class Visualisation for High Dimensional Data: Exploring Scientific Data Sets. Discovery Science Ata Kabán, Jianyong Sun, Somak Raychaudhury, Louisa Nolan
2006	C	`conf`	State Aggregation in Higher Order Markov Chains for Finding Online Communities. IDEAL Xin Wang, Ata Kabán
2005	—	`conf`	A Scalable Generative Topographic Mapping for Sparse Data Sequences. ITCC (1) Ata Kabán
2005	B	`conf`	A variational Bayesian method for rectified factor analysis. IJCNN Markus Harva, Ata Kabán
2005	C	`conf`	Finding Uninformative Features in Binary Data. IDEAL Xin Wang, Ata Kabán
2005	A	`conf`	Finding Young Stellar Populations in Elliptical Galaxies from Independent Components of Optical Spectra. SDM Ata Kabán, Louisa Nolan, Somak Raychaudhury
2005	J	`jnl`	Semisupervised Learning of Hierarchical Latent Trait Models for Data Visualization. IEEE Trans. Knowl. Data Eng. Ian T. Nabney, Yi Sun, Peter Tiño, Ata Kabán
2005	J	`jnl`	Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains. Data Min. Knowl. Discov. Mark A. Girolami, Ata Kabán
2004	A*	`conf`	A generative probabilistic approach to visualizing sets of symbolic sequences. KDD Peter Tiño, Ata Kabán, Yi Sun
2004	B	`conf`	Context based identification of user communities from Internet chat. IJCNN Ata Kabán, Xin Wang
2004	A	`conf`	Learning to Read Between the Lines: The Aspect Bernoulli Model. SDM Ata Kabán, Ella Bingham, T. Hirsimäki
2004	A	`ed.`	Parallel Problem Solving from Nature - PPSN VIII, 8th International Conference, Birmingham, UK, September 18-22, 2004, Proceedings PPSN Xin Yao, Edmund K. Burke, José Antonio Lozano, Jim Smith, Juan Julián Merelo Guervós, John A. Bullinaria, Jonathan E. Rowe, Peter Tiño, Ata Kabán, Hans-Paul Schwefel
2003	B	`conf`	An Adaptive Novelty Detection Approach to Low Level Analysis of Images Corrupted by Mixed Noise. KES Alexander N. Dolia, Martin Lages, Ata Kabán
2003	A*	`conf`	On an equivalence between PLSI and LDA. SIGIR Mark A. Girolami, Ata Kabán
2003	—	`conf`	Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles. NIPS Mark A. Girolami, Ata Kabán
2003	J	`jnl`	Topic Identification in Dynamical Text by Complexity Pursuit. Neural Process. Lett. Ella Bingham, Ata Kabán, Mark A. Girolami
2002	J	`jnl`	A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams. J. Intell. Inf. Syst. Ata Kabán, Mark A. Girolami
2002	C	`conf`	A General Framework for a Principled Hierarchical Visualization of Multivariate Data. IDEAL Ata Kabán, Peter Tiño, Mark A. Girolami
2002	J	`jnl`	Fast Extraction of Semantic Features from a Latent Semantic Indexed Text Corpus. Neural Process. Lett. Ata Kabán, Mark A. Girolami
2001	J	`jnl`	A Combined Latent Class and Trait Model for the Analysis and Visualization of Discrete Data. IEEE Trans. Pattern Anal. Mach. Intell. Ata Kabán, Mark A. Girolami
2001	—	`conf`	Finding Topics in Dynamical Text: Application to Chat Line Discussions. WWW Posters Ella Bingham, Ata Kabán, Mark A. Girolami
2001	J	`jnl`	Sign-changing filters similar to cells in primary visual cortex emerge by independent component analysis of temporally convolved natural image sequences. Neurocomputing András Lörincz, Botond Szatmáry, Ata Kabán
2000	B	`conf`	Initialized and Guided EM-Clustering of Sparse Binary Data with Application to Text Based Documents. ICPR Ata Kabán, Mark A. Girolami
2000	—	`conf`	The Organization and Visualization of Document Corpora: A Probabilistic Approach. DEXA Workshop Mark A. Girolami, Alexei Vinokourov, Ata Kabán