2 citations · 2 across the 1 of their papers we have counts for
5 papers
Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns
Ali Taylan Cemgil, Mehmet Burak Kurutmaz, Sinan Yildirim +2
We introduce a dynamic generative model, Bayesian allocation model (BAM), which establishes explicit connections between nonnegative tensor factorization (NTF), graphical models of…
Scalable Monte Carlo inference for state-space models
Sinan Yıldırım, Christophe Andrieu, Arnaud Doucet
We present an original simulation-based method to estimate likelihood ratios efficiently for general state-space models. Our method relies on a novel use of the conditional Sequent…
Image Segmentation with Pseudo-marginal MCMC Sampling and Nonparametric Shape Priors
Ertunc Erdil, Sinan Yildirim, Tolga Tasdizen +1
In this paper, we propose an efficient pseudo-marginal Markov chain Monte Carlo (MCMC) sampling approach to draw samples from posterior shape distributions for image segmentation.…
On the utility of Metropolis-Hastings with asymmetric acceptance ratio
Christophe Andrieu, Arnaud Doucet, Sinan Yıldırım +1
The Metropolis-Hastings algorithm allows one to sample asymptotically from any probability distribution . There has been recently much work devoted to the development of variant…
On the Use of Penalty MCMC for Differential Privacy
Sinan Yıldırım
We view the penalty algorithm of Ceperley and Dewing (1999), a Markov chain Monte Carlo (MCMC) algorithm for Bayesian inference, in the context of data privacy. Specifically, we st…