Sinan Yıldırım

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Journal

Differentially private online Bayesian estimation with adaptive truncation; Sinan Yıldırım; Turkish Journal of Electrical Engineering and Computer Sciences, 2024

A model of dynamic migration networks: Explaining Turkey's inter-provincial migration flows; Ozan Aksoy, S. Yıldırım; Sociological Methodology, 2024

Supply Curves in Electricity Markets: A Framework for Dynamic Modeling and Monte Carlo Forecasting; Sinan Yıldırım, Mohammad Khalafi, Tayyar Güzel, Halil Satık, Murat Yılmaz; IEEE Transactions on Power Systems, 2023

Statistic Selection and MCMC for Differentially Private Bayesian Estimation; Barış Alparslan, Sinan Yıldırım; Statistics and Computing, 2022 (arxiv version, view-only version)

Differentially Private Accelerated Optimization Algorithms; Nurdan Kuru, İlker Birbil, Mert Gürbüzbalaban, Sinan Yıldırım; SIAM Journal on Optimization, 2022 (accepted paper, arxiv version)

Machine learning-based load distribution and balancing in heterogeneous database management systems; A Abdennebi, A Elakaş, F Taşyaran, E Öztürk, K Kaya, S Yıldırım; Concurrency and Computation: Practice and Experience, 2022

A real-world application of Markov chain Monte Carlo method for Bayesian trajectory control of a robotic manipulator; Vahid Tavakol Aghaei, Arda Ağababaoğlu, Sinan Yıldırım, Ahmet Onat; ISA Transactions, 2021

Bayesian Allocation Model: Marginal Likelihood-based Model Selection for Count Tensors; S. Yıldırım, M. Burak Kurutmaz, Melih Barsbey, Umut Şimşekli, A. Taylan Cemgil; IEEE Journal of Selected Topics in Signal Processing, 2021

Pseudo-marginal MCMC Sampling for image segmentation using nonparametric shape priors; Ertunç Erdil, S. Yıldırım, Tolga Taşdizen, Müjdat Çetin; IEEE Transactions on Image Processing, 2019

Exact MCMC with differentially private moves; S. Yıldırım, Beyza Ermiş; Statistics and Computing, 2019 (view-only link)

A Markov chain Monte Carlo algorithm for Bayesian policy search; Vahid Tavakol, Ahmet Onat and S. Yıldırım; Systems Science and Control Engineering, 2018

Bayesian tracking and parameter learning for non-linear multiple target tracking models; Lan Jiang, Sumeetpal S. Singh, S. Yıldırım; IEEE Transactions on Signal Processing, 2015

Parameter estimation in hidden Markov Models with intractable likelihoods using sequential Monte Carlo; S. Yıldırım, S. Singh, T. Dean, A. Jasra; Journal of Computational and Graphical Statistics, 2015

Calibrating the gaussian multi-target tracking model; S. Yıldırım, L. Jiang, S. S. Singh, and T. A. Dean; Statistics and Computing, 2015 (view-only link)

An online expectation-maximisation algorithm for changepoint models; S. Yıldırım, S. S. Singh, and A. Doucet; Journal of Computational and Graphical Statistics, 2013

A Bayesian deconvolution approach for receiver function analysis; S. Yıldırım, A. T. Cemgil, M. Aktar, Y. Özakın, and A. Ertüzün; IEEE Transactions in Geoscience and Remote Sensing, 2010

Estimation of time varying AR SαS processes using Gibbs sampling; D. Gençağa, E. E. Kuruoğlu, A. Ertüzün, and S. Yıldırım; Signal Processing, 2008

Reports

Differential Privacy of Noisy (S)GD under Heavy-Tailed Perturbations; Umut Şimşekli, Mert Gürbüzbalaban, Sinan Yıldırım, Lingjiong Zhu; arXiv, 2022

Learning with Subset Stacking; S. Ilker Birbil, Sinan Yildirim, Kaya Gokalp, Hakan Akyuz; arXiv, 2022

Metropolis-Hastings with Averaged Acceptance Ratios; Christophe Andrieu, S. Yıldırım, Arnaud Doucet, Nicolas Chopin; arXiv, 2020

Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns; Ali Taylan Cemgil, Mehmet Burak Kurutmaz, S. Yıldırım, Melih Barsbey, Umut Şimşekli; arxiv, 2019

Scalable Monte Carlo inference in state-space models; S. Yıldırım, Christophe Andrieu, Arnaud Doucet; arxiv, 2018

On the utility of Metropolis-Hastings with asymmetric acceptance ratio; Christophe Andrieu, Arnaud Doucet, S. Yıldırım, Nicolas Chopin; arXiv, 2018

On the Use of Penalty MCMC for Differential Privacy; S. Yıldırım, arxiv; 2016

Conference

Differentially Private Distributed Bayesian Linear Regression with MCMC; Barış Alparslan, Sinan Yıldırım, Ş. İlker Birbil; ICML 2023, 2023 (arxiv version)

Differentially Private Frequency Sketches for Intermittent Queries on Large Data Streams; S. Yıldırım, Kamer Kaya, Soner Aydın, Hakan Buğra Erentuğ; IEEE International Conference on Big Data (Big Data), 2020

MCMC shape sampling for image segmentation with nonparametric shape priors; E. Erdil, S. Yıldırım, T. Taşdizen, M. Çetin; Computer Vision and Pattern Recognition (CVPR), 2016

A new particle filtering algorithm for multiple target tracking with non-linear observations; L. Jiang, S. S. Singh, S.Yıldırım; 17’th International Conference on Information Fusion, 2014

A Monte Carlo expectation-maximisation algorithm for parameter estimation in multiple target tracking; S. Yıldırım, L. Jiang, S. S. Singh, and T. Dean; 15’th International Conference on Information Fusion 2012

An online expectation-maximisation algorithm for nonnegative matrix factorisation models; S. Yıldırım, A. T. Cemgil, and S. S. Singh; SYSID, 2012

A hybrid method for deconvolution of Bernoulli-Gaussian processes; S. Yıldırım, A. T. Cemgil, and A. Ertüzün; IEEE ICASSP, 2009

Workshop papers

Image segmentation with pseudo-marginal MCMC sampling and nonparametric shape priors; Ertunç Erdil, S. Yıldırım, Tolga Taşdizen, Müjdat Çetin; NIPS Workshop on Advances in Approximate Bayesian Inference, 2017

Bayesian nonnegative matrix factorization as an allocation model; M. Burak Kurutmaz, A. Taylan Cemgil, Umut Şimşekli, S. Yıldırım; NIPS Workshop on Advances in Approximate Bayesian Inference, 2017

Bayesian Learning of Non-Negative Matrix/Tensor Factorizations by Simulating Polya Urns; M. Burak Kurutmaz, A. Taylan Cemgil, Melih Barsbey, Umut Şimşekli, S. Yıldırım; NIPS Workshop on Advances in Approximate Bayesian Inference, 2018

Theses

Maximum Likelihood Parameter Estimation in Time Series Models Using Sequential Monte Carlo, PhD, Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, UK, 2013

Bayesian Methods for Deconvolution of Sparse Processes, MSc, Department of Electrical and Electronics Engineering, Boğaziçi University, Turkey, 2009

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