Onur Dikmen

28 papers A* 1A 1Misc 2Journal 15Unranked 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
Context discovery for anomaly detection.
Int. J. Data Sci. Anal.
Ece Calikus, Slawomir Nowaczyk, Onur Dikmen
2022 J jnl
Wisdom of the contexts: active ensemble learning for contextual anomaly detection.
Data Min. Knowl. Discov.
Ece Calikus, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia, Onur Dikmen
2021 J jnl
Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection.
CoRR
Ece Calikus, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia, Onur Dikmen
2020 — conf
Interactive Anomaly Detection Based on Clustering and Online Mirror Descent.
IoT Streams/ITEM@PKDD/ECML
Lingyun Cheng, Sadhana Sundaresh, Mohamed-Rafik Bouguelia, Onur Dikmen
2020 J jnl
No free lunch but a cheaper supper: A general framework for streaming anomaly detection.
Expert Syst. Appl.
Ece Calikus, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Onur Dikmen
2019 A* conf
Differentially Private Markov Chain Monte Carlo.
NeurIPS
Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela
2019 J jnl
Differentially Private Markov Chain Monte Carlo.
CoRR
Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela
2019 J jnl
No Free Lunch But A Cheaper Supper: A General Framework for Streaming Anomaly Detection.
CoRR
Ece Calikus, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna, Onur Dikmen
2017 A conf
Differentially Private Variational Inference for Non-conjugate Models.
UAI
Joonas Jälkö, Antti Honkela, Onur Dikmen
2016 J jnl
Differentially Private Variational Inference for Non-conjugate Models.
CoRR
Joonas Jälkö, Onur Dikmen, Antti Honkela
2016 J jnl
Efficient differentially private learning improves drug sensitivity prediction.
CoRR
Antti Honkela, Mrinal Das, Onur Dikmen, Samuel Kaski
2015 J jnl
Learning Mixtures of Ising Models using Pseudolikelihood.
CoRR
Onur Dikmen
2015 J jnl
Learning the Information Divergence.
IEEE Trans. Pattern Anal. Mach. Intell.
Onur Dikmen, Zhirong Yang, Erkki Oja
2015 J jnl
Optimizing the Information Retrieval Trade-off in Data Visualization Using $α$-Divergence.
CoRR
Ehsan Amid, Onur Dikmen, Erkki Oja
2015 Misc conf
Sound event detection in real life recordings using coupled matrix factorization of spectral representations and class activity annotations.
ICASSP
Annamaria Mesaros, Toni Heittola, Onur Dikmen, Tuomas Virtanen
2014 J jnl
Learning the Information Divergence.
CoRR
Onur Dikmen, Zhirong Yang, Erkki Oja
2014 — conf
Sequential Monte Carlo samplers for marginal likelihood computation in multiplicative exponential noise models.
SSP
Onur Dikmen, Ali Taylan Cemgil
2013 — conf
Sound event detection using non-negative dictionaries learned from annotated overlapping events.
WASPAA
Onur Dikmen, Annamaria Mesaros
2012 — conf
Clustering by Nonnegative Matrix Factorization Using Graph Random Walk.
NIPS
Zhirong Yang, Tele Hao, Onur Dikmen, Xi Chen, Erkki Oja
2012 J jnl
Maximum Marginal Likelihood Estimation for Nonnegative Dictionary Learning in the Gamma-Poisson Model.
IEEE Trans. Signal Process.
Onur Dikmen, Cédric Févotte
2011 Misc conf
Maximum marginal likelihood estimation for nonnegative dictionary learning.
ICASSP
Onur Dikmen, Cédric Févotte
2011 — conf
Nonnegative dictionary learning in the exponential noise model for adaptive music signal representation.
NIPS
Onur Dikmen, Cédric Févotte
2010 J jnl
Gamma Markov Random Fields for Audio Source Modeling.
IEEE Trans. Speech Audio Process.
Onur Dikmen, Ali Taylan Cemgil
2009 — —
Bayesian source modelling for single-channel audio separation (Ses sinyallerinin tek kanaldan ayrıştırılmasında Bayesçi modeller)
Onur Dikmen
2009 — conf
Unsupervised single-channel source separation using bayesian NMF.
WASPAA
Onur Dikmen, Ali Taylan Cemgil
2007 — conf
Conjugate Gamma Markov Random Fields for Modelling Nonstationary Sources.
ICA
Ali Taylan Cemgil, Onur Dikmen
2007 J jnl
Parallel univariate decision trees.
Pattern Recognit. Lett.
Olcay Taner Yildiz, Onur Dikmen
2003 — conf
Estimating Distributions in Genetic Algorithms.
ISCIS
Onur Dikmen, H. Levent Akin, Ethem Alpaydin