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Browsing Bilgisayar Mühendisliği by Author "Cemgil, Ali Taylan."

Browsing Bilgisayar Mühendisliği by Author "Cemgil, Ali Taylan."

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  • A bayesian approach to the clustering problem with application to gene expression analysis 
    Fidaner, Işık Barış. (Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2016., 2016.)
    This thesis investigates methods for extraction of information from gene expression time series data. These time series provide indirect measurements about the underlying biological mechanisms, hence their analysis heavily ...
  • Acceleration of sequential Monte Carlo methods via parallelization of resampling algorithms 
    Güldaş, Hakan. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2015., 2015.)
    Sequential Monte Carlo (SMC) methods, also known as particle lters, are a popular set of tools in Bayesian inference on non-linear non-Gaussian state space models. While these algorithms are traditionally developed with ...
  • Algorithms for learning from online human behavior and human interaction with learning algorithms 
    Çapan, Gökhan. (Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022)
    In modern digital systems, algorithms that deliver personalized content shape the user experience and affect user satisfaction, hence long-term engagement with the system. What the system presents also influences the parties ...
  • Anomaly detection in time series 
    Poyraz, Onur. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2019., 2019.)
    Anomaly detection (AD) is the discovery of the observations which does not con form with the rest of the observations. The types of anomalies and their occurrences that exist in the data set are tried to be determined. On ...
  • Bayesian approaches for privacy preserving data sharing 
    Ermiş, Beyza. (Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2020., 2020.)
    In this thesis, we focus on the data fusion problem where we have heterogeneous data which is collected from di↵erent sources and stored in the form of matrices and higher-order tensors and propose coupled matrix and tensor ...
  • Bayesian methods for network traffic analysis 
    Kurt, Barış. (Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2019., 2019.)
    Statistical information about tra c patterns help a service provider to characterize its network resource usage and user behavior, infer future tra c demands, detect tra c and usage anomalies, and possibly provide insights ...
  • Bayesian methods for real-time pitch tracking 
    Şimşekli, Umut. (Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2010., 2010.)
    In this thesis, we deal with probabilistic methods to track the pitch of a musical instrument in real-time. Here, we take the pitch as a physical attribute of a musical sound which is closely related to the frequency ...
  • Bayesian model selection for latent variable causal networks by sequential Monte Carlo 
    Kurutmaz, Mehmet Burak. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2019., 2019.)
    Inferring the causal structure of several random variables is a challenging task when interventions are not feasible. Presence of latent confounders further increases the difficulty of the problem, and therefore is neglected ...
  • Biclustering using nonparametric Bayesian methods 
    Çelik, Safiye. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2012., 2012.)
    Multiway clustering is a popular analysis method due to its several potential applications. Various techniques have been developed to cluster di erent entities of a data matrix simultaneously by taking relational entries ...
  • Collaborative filtering and content based hybrid models for recommending scientific articles 
    Öğretir, Mine. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2018., 2018.)
    Recommendation systems (RS) are programs that assist users in accessing infor mation in vast amount of data collections. In this thesis, we investigate hybrid models that use both implicit ratings such as tags, bookmarks ...
  • Distance approximations between high and multi-dimensional structures 
    Semerci, Murat. (Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2019., 2019.)
    In this thesis, we focus on distance approximation methods between high and multi-dimensional structures and their applications. Two novel methods using distance approximations are proposed and they are applied to anomaly ...
  • Effects of the receiver characteristics, variation of target intensity and nonlinearity on probability hypothesis density filter compared to data association techniques 
    Öksüz, Kemal. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2016., 2016.)
    Target tracking algorithms adopted in modern radars are designed such that they can track multitarget by considering target births and target deaths. These algorithms are derived by integrating the data association techniques ...
  • Endosensorfusion: Particle filtering - based multi - sensory data fusion with switching state - space model for endoscopic capsule robots using recurrent neural network kinematics 
    Almalıoğlu, Yasin. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2017., 2017.)
    Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the gastrointestinal (GI) tract and diagnosis of a wide range of diseases and pathologies. Medical device ...
  • Fast high-dimensional temporal point processes with applications 
    Türkmen, Ali Caner. (Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2020., 2020.)
    Large sets of continuous-time discrete event streams are often in the focus of seismology, neuroscience, finance, behavioral science among other scientific and engi neering disciplines. In this work, we explore a set of ...
  • Generalized tensor factorization 
    Yılmaz, Yusuf Kenan. (Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2012., 2012.)
    This thesis proposes a unified probabilistic framework for modelling multiway data. Our approach establishes a novel link between probabilistic graphical models and tensor factorization, that allows us to design arbitrary ...
  • Inference and parameter estimation in bayesian change point models 
    Yıldız, Çağatay. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2017., 2017.)
    In this work, we present a Bayesian change point model that identifies the time points at which a time series undergoes abrupt changes. Our model is a hierarchical hidden Markov model that treats the change points and the ...
  • Model selection for relational data factorization models 
    Hızlı, Çağlar. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2020., 2020.)
    For relational data factorization, generative models provide a statistically principled approach that allows for extending the factorization task in the probabilistic framework of Bayesian statistics. The most well-known ...
  • Modeling bounded data with sum conditioned poisson factorization 
    Ceritli, Taha Yusuf. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2017., 2017.)
    Non-negative matrices appears in many domains from item recommendation, audio signal processing to computer vision in which data instances have a bounded non-negative range. For various tasks in these areas, probabilistic ...
  • Parallel resampling for real - time sequential Monte Carlo 
    Bozkurt, Alper Kamil. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2018., 2018.)
    Sequential Monte Carlo (SMC) methods are well known and widely used for state estimation in nonlinear/non-Gaussian dynamical systems. However due to the heavy computational requirements, they may not satisfy the real-time ...
  • Probabilistic tensor factorization for link prediction 
    Ermiş, Beyza. (Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2012., 2012.)
    Link prediction is the problem of inferring the presence, absence or strength of a link between two entities, based on properties of the other observed links. In the literature, two related types of link prediction problems ...

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