Estimating Distributions in Genetic Algorithms. - Onur Dikmen; H. Levent Akin; Ethem Alpaydin (ISCIS, 2003)

Conjugate Gamma Markov Random Fields for Modelling Nonstationary Sources. - Ali Taylan Cemgil; Onur Dikmen (ICA, 2007)

Parallel univariate decision trees. - Olcay Taner Yildiz; Onur Dikmen (Pattern Recognit. Lett., 2007)

Unsupervised single-channel source separation using bayesian NMF. - Onur Dikmen; Ali Taylan Cemgil (WASPAA, 2009)

Bayesian source modelling for single-channel audio separation (Ses sinyallerinin tek kanaldan ayrıştırılmasında Bayesçi modeller) - Onur Dikmen (2009)

Gamma Markov Random Fields for Audio Source Modeling. - Onur Dikmen; Ali Taylan Cemgil (IEEE Trans. Speech Audio Process., 2010)

Maximum marginal likelihood estimation for nonnegative dictionary learning. - Onur Dikmen; Cédric Févotte (ICASSP, 2011)

Nonnegative dictionary learning in the exponential noise model for adaptive music signal representation. - Onur Dikmen; Cédric Févotte (NIPS, 2011)

Clustering by Nonnegative Matrix Factorization Using Graph Random Walk. - Zhirong Yang; Tele Hao; Onur Dikmen; Xi Chen 017; Erkki Oja (NIPS, 2012)

Maximum Marginal Likelihood Estimation for Nonnegative Dictionary Learning in the Gamma-Poisson Model. - Onur Dikmen; Cédric Févotte (IEEE Trans. Signal Process., 2012)

Sound event detection using non-negative dictionaries learned from annotated overlapping events. - Onur Dikmen; Annamaria Mesaros (WASPAA, 2013)

Sequential Monte Carlo samplers for marginal likelihood computation in multiplicative exponential noise models. - Onur Dikmen; Ali Taylan Cemgil (SSP, 2014)

Sound event detection in real life recordings using coupled matrix factorization of spectral representations and class activity annotations. - Annamaria Mesaros; Toni Heittola; Onur Dikmen; Tuomas Virtanen (ICASSP, 2015)

Optimizing the Information Retrieval Trade-off in Data Visualization Using $α$-Divergence. - Ehsan Amid; Onur Dikmen; Erkki Oja (CoRR, 2015)

Learning Mixtures of Ising Models using Pseudolikelihood. - Onur Dikmen (CoRR, 2015)

Learning the Information Divergence. - Onur Dikmen; Zhirong Yang; Erkki Oja (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Efficient differentially private learning improves drug sensitivity prediction. - Antti Honkela; Mrinal Das; Onur Dikmen; Samuel Kaski (CoRR, 2016)

Differentially Private Variational Inference for Non-conjugate Models. - Joonas Jälkö; Antti Honkela; Onur Dikmen (UAI, 2017)

Differentially Private Markov Chain Monte Carlo. - Mikko A. Heikkilä; Joonas Jälkö; Onur Dikmen; Antti Honkela (NeurIPS, 2019)

Interactive Anomaly Detection Based on Clustering and Online Mirror Descent. - Lingyun Cheng; Sadhana Sundaresh; Mohamed-Rafik Bouguelia; Onur Dikmen (IoT Streams/ITEM@PKDD/ECML, 2020)

No free lunch but a cheaper supper: A general framework for streaming anomaly detection. - Ece Calikus; Slawomir Nowaczyk; Anita Pinheiro Sant'Anna; Onur Dikmen (Expert Syst. Appl., 2020)

Wisdom of the contexts: active ensemble learning for contextual anomaly detection. - Ece Calikus; Slawomir Nowaczyk; Mohamed-Rafik Bouguelia; Onur Dikmen (Data Min. Knowl. Discov., 2022)

Context discovery for anomaly detection. - Ece Calikus; Slawomir Nowaczyk; Onur Dikmen (Int. J. Data Sci. Anal., 2025)