98 citations · 208 across the 11 of their papers we have counts for
6 papers · 1 filter
A Bayesian Choice Model for Eliminating Feedback Loops
Gökhan Çapan, Ilker Gündoğdu, Ali Caner Türkmen +2
Self-reinforcing feedback loops in personalization systems are typically caused by users choosing from a limited set of alternatives presented systematically based on previous choi…
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…
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization
Umut Şimşekli, Çağatay Yıldız, Thanh Huy Nguyen +2
Recent studies have illustrated that stochastic gradient Markov Chain Monte Carlo techniques have a strong potential in non-convex optimization, where local and global convergence…
Differentially Private Variational Dropout
Beyza Ermis, Ali Taylan Cemgil
Deep neural networks with their large number of parameters are highly flexible learning systems. The high flexibility in such networks brings with some serious problems such as ove…
Differentially Private Dropout
Beyza Ermis, Ali Taylan Cemgil
Large data collections required for the training of neural networks often contain sensitive information such as the medical histories of patients, and the privacy of the training d…
Alpha/Beta Divergences and Tweedie Models
Y. Kenan Yilmaz, A. Taylan Cemgil
We describe the underlying probabilistic interpretation of alpha and beta divergences. We first show that beta divergences are inherently tied to Tweedie distributions, a particula…