Mühendislik FakültesiBilgisayar Mühendisliği

Bilgisayar Mühendisliği





Seminer Tarihi: 13 Eylül 2017 

Seminer Konusu:  “Stabilizing Distributed Systems”   

Konuşmacı: Prof. Dr. Hakan Karaata, Professor in the Department of Computer Engineering at Kuwait University





Seminer Tarihi: 21 Nisan 2017 

Seminer Konusu:  Yazılım geliştirme yaşam döngüsü   

Konuşmacı: Özgün Emre Uğurlu, NETAŞ


Seminer Tarihi: 21 Nisan 2017 

Seminer Konusu:  Redis, SignalR  teknolojileri uygulamaları   

Konuşmacı: Ersel Bozkartal, NETAŞ


Seminer Tarihi: 21 Nisan 2017 

Seminer Konusu:  Profesyonel iş hayatında bizi neler bekliyor?   

Konuşmacı: Hakan Altınbaş, NETAŞ



Seminer Tarihi: 14 Nisan 2017 

Seminer Konusu:  Yeni Sanayi Devrimi : Sanayinin Sayısal Dönüşümü   

Konuşmacı: Alper Gerçek,  Kıdemli Tasarım Lideri, Teknoloji Transfer Müdürlüğü, Aselsan


Seminer Tarihi: 7 Nisan 2017 

Seminer Konusu:  Türkiye IT pazarı ve Teknoloji Trendleri   

Konuşmacı: Aslı Demir KoçkalResearch Manager, Systems & Infrastructure Solutions, IDC


Seminer Tarihi: 7 Nisan 2017 

Seminer Konusu: Büyük Veri ve Analiz (Big Data & Analytics)

Konuşmacı: Dr. Çağatay Talay,  Senior Data Architect - Big Data Platform at Digiturk

Seminer Tarihi: 17 Mart 2017 

Seminer Konusu: Teknoloji Dönüşümünde BT Güvenliğinin Yeri

Konuşmacı: Yeşim Öztürk, Yazılım Pazarından Sorumlu Kıdemli Araştırma Analisti, IDC


Seminer Tarihi: 10 Mart 2017 

Seminer Konusu: Bilgi Güvenliği ve Kalite

Konuşmacı: Hatice Ezgi Civelek, Türkiye Sınai ve Kalkınma Bankası Bilgi Güveliği ve Kalite Birimi


Seminer Tarihi: 24 Şubat 2017 

Seminer Konusu: 5G Teknolojileri ve IoT, FPGA Programlama, Yapay Zeka Uygulamaları

Konuşmacı: Ali TELLİ, Ar-Ge Bölümü Yöneticisi, HAVELSAN


Seminer Tarihi: 17 Şubat 2017 

Seminer Konusu: Siber Güvenlik

Konuşmacı: Alper Başaran, Garnizon Bilgi Güvenliği




Seminer Tarihi: 26 Aralik 2016  

Seminer Konusu:  Combining Two Different Techniques for Image Segmentation

Özet: Clustering is the process of combining some set of data which show similar characteristics into one set, while seperating them among other parts of the data. Clustering is the main topic of data mining. Also it is a very crucial task for many other fields such as computer vision, image processing, pattern recognition, machine learning, etc. Clustering is called 'image segmentation' in image processing or computer vision. Image segmentation can be defined as the task of dividing image into different homogeneous regions containing several patches, whereas union of any two regions are non-homogeneous. Image segmentation plays a key role for many low-level computer vision applications such as object recognition, object tracking, medical imaging, face recognition and detection, etc. Since, homogenity criteria is application specific, image segmentation is a very hard job for low-level vision.  Existing image segmentation algorithms can be generally classified into three major categories, i.e., feature space based clustering, spatial segmentation, and graph-based approaches. Feature space based clustering approaches operate based on the color or texture, so that they ignore spatial information. There are parametric and non-parametric methods for feature space analysis. Parametric methods used in feature space analysis can lead to very wrong results due to parameters estimated by user. Parametric methods rely on training set for the parameters which must be well-tuned. Also, they are not suitable for arbitrary structured spaces. Sometimes, due to feature space overlap, discontinuities in the image are not preserved and irrelevant patches can be grouped together. So, a non-parametric, discontinuity preserving multi-mode seeking algorithm, so called mean shift, was proposed to find modes in the complex arbitrary structured density. However, for a good segmentation we must exploit spatial information also. Graph based approaches try to exploit both feature space and spatial information. In graph-based approaches pixels or regions are considered as vertexes and weight of edges are calculated based on both color or texture (feature space) and spatial distance. After constructing graph and its weight, the graph is partitioned into several homogeneous regions by minimizing some energy function. Normalized cut(Ncut) was the graph-based method considered in this study. Normalized cut is superior to other graph-based methods, however it is very source demanding. It is impractical to use Ncut for images whose size is bigger than 150x150. Hence, to overcome this deficit, in this work first, image is segmented coarsely by using mean shift and then Ncut was run on the regions found by mean shift. Running Ncut on regions rather than pixels reduced computation time drastically.   

Konuşmacı: Abdulvahid Uçar

Seminer Tarihi: 26 Aralik 2016  

Seminer Konusu:  Power Characteristics and Modeling during Data Transmission over WiFi and Cellular Networks

Özet: Energy consumption on smartphones is increasing rapidly with the increasing usage of applications that accessing the Internet over WiFi or cellular connection.  This causes the reduction of battery life of smartphones.  Current battery technology is not sufficient to meet the energy needs of networked applications for a long time. When the applications that need the network connectivity run for a long period, batteries in smartphones are draining before the end of the day. Therefore, the applications on smartphones should be made more energy efficient. To develop energy-efficient applications on smartphones, it must be known the factors affecting energy efficiency. There are some studies on this subject. In these studies, the energy consumption characteristics of data transmission over WiFi and cellular (HSDPA, LTE and so on) networks are investigated and some metrics affecting energy efficiency are identified, such as signal strength, traffic burstiness, network throughput and etc. Besides, performance and power characteristics of WiFi and the cellular networks are derived via measurements. Also, it is presented the power models of data transmission over WiFi and the cellular networks. In addition, an energy-aware scheduling algorithm is developed that computes optimal communication schedule for energy savings on the cellular networks.

Konuşmacı: Kübra Uludağ

Seminer Tarihi: 26 Aralik 2016  

Seminer Konusu:  Incentive Mechanisms for User-Provided Networks

Özet: By the great increase of usage smart mobile devices, internet connection is added to the list of commodities which people can share. In such user provided networks (UPNs), people generally share their internet connections with people who are known by the providers without profit making purpose. In order to make UPNs ubiquitous, there must be incentive mechanisms that encourage people to participate actively these kinds of networks and induce them to own crucial roles in the network which allows people to access to the internet provided by any user in UPN. In this presentation, I will present the roles and challenges of UPNs, how difficult to design such an incentive mechanism, proposed bargaining based scheme to set a fair medium between internet connection providers and consumers and virtual currency for satisfaction of participants.

Konuşmacı: Kenan Cebeci

Seminer Tarihi: 19 Aralik 2016  

Seminer Konusu:  Opinion Mining

Özet:  “Opinion Mining” is an interested area since online shopping sites and also microblogs have become widespread. Many people use this shopping sites (hepsiburada, amazon, ..) to buy what he/she wants. And also there are nearly hundreds of comments almost every product which helps to people to decide whether or not to buy the item, product or service. This customer reviews describe the experiences with the product/service are includes many important data like the product’s features. Feature selection is an important step in opinion mining (there are many steps in opinion mining and it is still growing). Customers express product opinions separately according to individual features of the product (for example: camera, ram, capacity can be features for the mobile phones). And try to find what customers say about of the features of a product or a service details about which aspects of a product people felt good or bad (or neutral).

Konuşmacı: Muhammet Alkan

Seminer Tarihi: 19 Aralik 2016 

Seminer Konusu:  A Review on Predicting Student Graduation in Higher Education Using Data Mining

Özet: Data Mining is increasingly used in higher institution to discover valuable information particularly in student databases. It brings to the concept of Educational Data Mining (EDM). EDM is a field that analyzes educational data to resolve its research issues using statistical, machine learning, and data mining algorithms. The emergence of EDM creates a good environment to all stakeholders in higher institution. One of them is graduation information. The data of graduated students from each academic year is an important source of information used as indicators of the school effectiveness by state and federal governments and accrediting agencies. Therefore, data mining can be used as an effective tool to predict graduation information of students to give insights to all stakeholders in higher institution whether the students are able to graduate on time, fast, late or even drop out from school. As a result, it assists the students on selecting suitable courses or field of study to their successful academic paths. In addition, it also assists the instructors to organize the curricula more effective to improve student academic performance. The purpose of this presentation is to provide an overview on data mining techniques that have been used to predict graduation information in higher institution through a survey of literature.

Konuşmacı: Izhan  Fakhruzi

Seminer Tarihi: 16 Aralik 2016

Seminer Konusu: “TUBITAK, BİLGEM Tanitimi ve Projeleri” 

Konuşmacı: Alper Ay, Birim Yoneticisi, TÜBİTAK

Seminer Tarihi: 12 Aralık 2016

Seminer Konusu :  Solving Graph Coloring Problem by Using Evolutionary Algorithms

Özet: The graph coloring problem is one of the well-known optimization problems from the literature that tries to assign different colors to the vertices connected through an edge in a given graph. Its aim is to use minimum number of colors to color the vertices in the graph. This problem can be used to solve many practical and theoretical problems. The graph coloring problem is an NP-complete problem and genetic algorithms are widely used to solve the graph coloring problem. In this presentation, we will explore the proposed solutions for graph coloring problem. The papers try to solve two types of graphs. The first graph model is a weighted static graph where each node has a cost. The algorithms use novel based crossover and local search techniques to find a better solution for this graph. The second model is a dynamic graph where each node has a life time to stay alive with its edges in. At each time step, number of nodes and number of edges in the graph change according to relative parameters. Some standart crossover and mutation techniques described in the literature are applied to this graph and it is the first and recently published paper that tries to solve dynamic graph coloring problem.   

Konuşmacı: Gizem Süngü

Seminer Tarihi: 12 Aralık 2016

Seminer Konusu:  Device To Devıce (D2D) Communıcatıon In Lte-Advanced Networks

Özet: D2D communication in cellular networks provides devices directly communicating without base stations or another appliance. D2D communication technology is an important feature to LTE-Advanced systems. High performance, increased coverage, high data rate support, wireless peer-to-peer services are some of the advantages of this technology. With this advantages compared to available communication techniques, it has a wide range usage area such as network traffic offloading, public safety deployments, social networking, military applications, context-aware applications, multimedia applications. For example, a user may be informed about discounts while he/she in the supermarket, or she/he can share videos/photos with nearby friends using D2D in LTE-A technology. Many social networking applications need to discover and register users’ geographical locations, but this process typically made by user’s itself manually. This can be done automatically  using D2D Proximity Services. From a technical perspective, with communicating via D2D in LTE-A, UEs (user equipment or mobile users) gain high data rates, low battery consumption and less delays. The goal of my presentation is to give an overview about D2D communication in LTE-Advanced networks standards and specs which are defined in 3GPP Release 12, and continues working with Release 13, and analyze related  research works about device discovery mechanism in this area.

Konuşmacı: Melike Sinem Uçum

Seminer Tarihi: 9 Aralik 2016

Seminer Konusu: “Fikri ve Mulki Haklar, Patent, Faydali Model” 

Konuşmacı: Ersin Dereligil, Yonetim Kurulu Uyesi, DESTEK PATENT

Seminer Tarihi: 2 Aralik 2016

Seminer Konusu: "IGA Teknoloji ve Servisleri" 

Konuşmacı: Ersin Inankul, IGA IT Direktoru, İstanbul Grand Airport

Seminer Tarihi: 25 Kasim 2016

Seminer Konusu: "Connected People - Connected World" 

Konuşmacılar: Kutsal Anıl, Genel Müdür, PAVOTEK


Seminer Tarihi: 7 Kasım 2016

Seminer Konusu: "Performance Analysis of Nature Inspired Heuristics for Survivable Virtual Topology Mapping"

Seminer Özeti:  The high capacity of fibers used in optical networks, can be divided into many channels, using the WDM technology. Any damage to a fiber causes all the channels routed through this link to be broken, which may result in a serious amount of data loss. As a solution to this problem, the virtual layer can be mapped onto the physical topology, such that, a failure on any physical link does not disconnect the virtual topology. This is known as the survivable virtual topology mapping problem. In this study, we investigated the performance of two popular nature inspired heuristics, namely, evolutionary algorithms and ant colony optimization, in finding a survivable mapping of a given virtual topology while minimizing the resource usage. Our results show that both nature inspired heuristics perform remarkably well for this problem. Furthermore, both methods can obtain high quality solutions in less than a minute.

Konuşmacılar: Yrd.Doç.Dr. Fatma Corut Ergin, Marmara Üniversitesi, Bilgisayar Mühendisliği Bölümü, Öğretim Üyesi 

Seminer Tarihi: 7 Kasım 2016

Seminer Konusu: "Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks"

Seminer Özeti:  Sensor nodes in a Wireless Sensor Network (WSN) can be dispersed over a remote sensing area e.g. the regions that cannot be accessed by human beings (inaccessible regions). In such kind of networks, data collection becomes one of the major issues. Getting connected to each sensor node and retrieving the information in time introduces new challenges. Mobile sink usage, especially the Unmanned Aerial Vehicle (UAV), is the most convenient approach to cover the area and access each sensor node in such a large scale WSN. However, the operation of the UAV depends on some parameters such as endurance time, altitude, speed, radio type in use, and the path. In this paper, we explore various mobility patterns of UAV that follow different paths to sweep the playground in order to seek the best area coverage with maximum number of covered nodes in less amount of time needed by the mobile sink. A realistic simulation environment is used in order to compare and evaluate the performance of the system. We present the performance results for the explored UAV mobility patterns. The results are very useful to present the tradeoff between maximizing the covered nodes and minimizing the operation time for choosing the appropriate mobility pattern.

Konuşmacılar: Yrd.Doç.Dr. Müjdat Soytürk, Marmara Üniversitesi, Bilgisayar Mühendisliği Bölümü, Öğretim Üyesi 

Seminer Tarihi: 31 Ekim 2016

Seminer Konusu: "Semantic Text Mining: Supervised and Semi-Supervised Classification Approaches"

Konuşma özeti:  Ever increasing volumes of structured and unstructured data in variety of types such text, multimedia, and graph is popularly referred as "Big Data".  An important portion of this data is in unstructured text format. There are important challenges to extract meaning or useful information from large textual datasets. One of the major methods used for organizing and mining big textual data is text classification. We use classification algorithms from machine learning domain which is a sub-field of Artificial Intelligence. In order for machine learning algorithms to work, unstructured textual documents are represented using Vector Space Models (VSM). Semantics of VSM comes from the distributional hypothesis, which states that words that occur in similar contexts usually have similar meanings. Although, the VSM  approach is very simple and commonly used, it has several limitations. One of them is the assumption of independency between terms as well as between documents. Documents are represented only with their term frequencies, disregarding their position in the document or their semantic or syntactic connections between other words. As a result, polysemous words (i.e. words with multiple meanings) are treated as a single entity and synonymous words are mapped into different components. This has a negative impact on performance of machine learning algorithms. There is a need for more advanced methods that incorporates additional semantics into these algorithms. In this seminar, we present several semantic text mining algorithms ranging from higher-order co-occurrence based probabilistic methods to class semantics based kernel methods for supervised and semi-supervised classification of textual documents.

Konuşmacılar: Yrd.Doç.Dr. Murat Can Ganiz, Marmara Üniversitesi, Bilgisayar Mühendisliği Bölümü, Öğretim Üyesi 

 Seminer Tarihi: 31 Ekim 2016

Seminer Konusu: "Migrating Birds Optimization: A New Meta-heuristic Approach and Its Application to the Quadratic Assignment Problem"

Seminer Konusu:  We propose a new nature inspired metaheuristic approach based on the V flight formation of the migrating birds which is proven to be an effective formation in energy saving. Its performance is tested on quadratic assignment problem instances arising from a real life problem and very good results are obtained. The quality of the solutions we report are better than simulated annealing, tabu search, genetic algorithm, scatter search, particle swarm optimization, differential evolution and guided evolutionary simulated annealing approaches. The proposed method is also tested on a number of benchmark problems obtained from the QAPLIB and in most cases it was able to obtain the best known solutions. These results indicate that our new metaheuristic approach could be an important player in metaheuristic based optimization.

Konuşmacılar: Doç.Dr. Ali Fuat Alkaya, Marmara Üniversitesi, Bilgisayar Mühendisliği Bölümü, Öğretim Üyesi  

Seminer Tarihi: 24 Ekim 2016

Seminer Konusu: "Affective Computing: Challenges, Applications, Approaches"

Seminer Özeti:  In human-human interactions we communicate using verbal messages and also non-verbal messages such as facial expressions, changes in our voice, and body gestures. The non-verbal messages reinforce or modify what is said in words. In the near future, it is envisioned that human-machine interaction will go beyond the mouse and the keyboard and will become more similar to human-human interaction. Machines will be aware of the emotional and mental state of humans and will adopt their responses accordingly. Affective computing is a relatively new research field the aim of which is to design systems that can recognize, interpret and simulate human emotions and related phenomena. In the first part of the seminar an introduction to the field of affective computing will be made, focusing on the application areas, and major research challenges.  In order to design systems which can recognize emotions, naturalistic training and test data are needed. Most databases available to researchers today are recorded in an acted way under laboratory conditions, and do not reflect real-world conditions. In the second part of the seminar, two new naturalistic affective audio-visual databases BAUM-1 and BAUM-2 will be introduced, which contain spontaneous Turkish expressions of 13 emotions and mental states. Then, three recent methods for multimodal audio/visual affect recognition will be described which use facial expressions and speech and fuse them at the decision level.

Konuşmacılar: Prof.Dr. Çiğdem Eroğlu Erdem, Marmara Üniversitesi, Bilgisayar Mühendisliği Bölümü, Öğretim Üyesi  

Seminer Tarihi: 24 Ekim 2016

Seminer Konusu: "Research Guide for Graduate Students"

Seminer Özeti:  The aim of this presentation is to introduce strategies for graduate students to succeed in their study. The content is  based on both experience of the advisors on their graduate students and set of documents related with the topic. The research process will be covered by presenting a set of related issues  including  managing day-to-day work life of a graduate student,  communication with his/her advisor, reading technical papers, plagiarism, publishing results of research and professional development.   Unlike undergraduate courses,  graduate studies require a student read large volumes of technical documents.   As part of the presentation, critical reading strategies are briefly presented. Writing at the Master’s or PhD level is a challenging process, which will be covered briefly as the last phase  of the presentation

Konuşmacılar: Prof.Dr. Haluk Topçuoğlu, Marmara Üniversitesi, Bilgisayar Mühendisliği Bölümü, Bölüm Başkanı

 Seminer Tarihi: 14 Ekim 2016

Seminer Konusu: “CDN and  Cloud Technology”

Konuşmacılar: Atakan TİTİZ, DoraBase, IT Departman Direktörü

Seminer Tarihi: 7 Ekim 2016

Seminer Konusu: “IoT and Mobile Communication”

Konuşmacılar: Serhat Türkiçin, Turkcell, M2M ve IoT Servisleri ve Çözümleri Bölümü Yöneticisi. 

Seminer Tarihi: 30 Eylül 2016

Seminer Konusu: “CSE497 ve CSE498 Bitirme Projesi Hazırlama Süreçleri”

Konuşmacılar: Yrd. Doç. Dr. Müjdat Soytürk, Öğr. Gör. Birol Gençyılmaz



Seminer Tarihi: 5 Mayıs 2016

Seminer Konusu: "Vulnerability Analysis of Soft Errors"

Seminer Özeti:  As the technology advances, the transistors become smaller and the system becomes more vulnerable to the soft errors. Soft errors are transient errors that occur as bit flip in the memory and caused program's behaviour become unreliable. To prevent these errors some fault tolerance techniques are proposed. These techniques generally introduce information or hardware overhead to the system and increases the cost significantly. Consequently, selective reliability is proposed to reduce the overhead.  Some of the bit flips that occur at microarchitectural structures, don't affect the output of the program. The Architectural Vulnerability Factor (AVF) is the probability of a fault in structure affect the output. With this metric fault tolerance and recovery techniques may only apply most vulnerable parts and the overhead decreases. AVF provides error propagation probability of structures, however when it applies to the cache memories and register files, it cannot calculate probability accurately because of the characteristics of these structures. Hence, Cache Vulnerability Factor (CVF) and Register Vulnerability Factor are proposed to calculate the probability of error propagate to other components for cache and register respectively.  The vulnerability analysis also applies to the software level to quantify the vulnerability of a program.

Konuşmacı: Zuhal Öztürk

Seminer Tarihi: 5 Mayıs 2016

Seminer Konusu: "Preserving High Performance in Cloud Computing with Optimal Power Consumption"

Seminer Özeti:  Cloud computing is one of the most studied subjects of all computing paradigms today. Even though researchers have intensive interest on this area, still there are many issues that have difficult challenges await to be solved. Power consumption of cloud computing systems is one of these issues. While managing energy consumption efficiently, cloud systems should not experience performance loss. In this presentation, IaaS(Infrastructure as a Service) -one of the core services of a cloud computing system- and virtualization will be introduced briefly. State-of-the-art techniques for energy saving in the cloud computing computing systems will be presented. Trade-offs of virtual machine consolidation between performance and power consumption will be discussed.

Konuşmacı: Mustafa Gamsız

Seminer Tarihi: 29 Nisan 2016

Seminer Konusu: “Robotics and Artificial Intelligence”

Konuşmacı: Nezih Ergin Özkucur, Boğaziçi Üni. Computer Eng. PhD student 

Seminer Tarihi: 28 Nisan 2016

Seminer Konusu: "Fireworks Algorithm for Optimization Problems"

Seminer Özeti:  A novel swarm intelligence algorithm, called Fireworks Algorithm (FWA), is proposed for global optimization of complex problems. A comprehensive study on FWA revealed that the algorithm works surprisingly well on benchmark functions. The details of Fireworks Algorithm will be introduced. However, FWA has some limitations. A set of improvements applied on conventional FWA, named Enhanced FWA (EFWA) will be decribed. Also, three other variants of FWA, called Dynamic Search FWA (dynFWA) and Adaptive FWA (AFWA) and a novel GPU-based Fireworks Algorithm (GPU-FWA) will be presented and compared with conventional FWA.

Konuşmacı: Hakan Pekdemir

Seminer Tarihi: 28 Nisan 2016

Seminer Konusu: "MPI-Based Parallel Brain Simulations with NEURON"

Seminer Özeti:  Neurons (also known as nerve cells) are the cells that participate in the construction of the central and peripheral nervoussystem. Gathering information about neurons, helps us to understand causes and effects of the neurological diseases. Simulation of neurons and networks of can be used to gather information about neurons with the help of simulation tools such as NEURON. NEURON is a brain simulator that is widely used by neuroscientist. It is possible to simulate neurons and networks of them as if they exist by using NEURON. Unfortunately, simulation of neurons requires more computational resources as the number of neurons in simulation models increase and also requires more time to complete simulations. To overcome this problem, parallel simulations of models can be conducted. NEURON uses MPI (Message Passing Interface) library to provide communication between processors in parallel simulations. Neurons, NEURON simulator and MPI standard will be presented as parts of the seminar course presentation.

Konuşmacı: Serap Korkmaz

Seminer Tarihi: 21 Nisan 2016

Seminer Konusu: "Broadband Access Networks"

Seminer Özeti:  The evolution of the access network towards broadband is one of the most crucial and demanding challenges in the battle between the actors in the telecommunications industry. The issue of establishing access networks for broadband services is complex, both in terms of the broadband service market, and in terms of the future regulation of the customer access to telecommunications infrastructure. Moreover, there is a wide range of technologies available for broadband access, which further complicates the issue of broadband access. Broadband access technologies enable data, voice, video and other multimedia applications for home and business use. There are several rival technologies that are competing to deliver broadband connections each with its own distinct advantages and disadvantages. The choice of what access technologies to deploy depends mainly on its commercially viability and which access technology can best serve the current and future consumer demands.

Konuşmacı: Merve Günaydın

Seminer Tarihi: 21 Nisan 2016

Seminer Konusu: "Convolutional Neural Networks"

Seminer Özeti: Convolutional Neural Networks (CNN) is one of the popular feedforward neural networks. CNN has demonstrated good performance on image classification in the large scale visual recognition challenge (ILSVRC2012) which is competition of ImageNet in 2012 and the goal of this competition is to estimate context of images. CNN’s success is the learning ability of the rich mid-level image representation. CNNs learn but they need huge amount of annotated image samples and they need millions of parameters for estimation. New generated GPUs have highly optimized implementation of 2D convolution and their performance is adequate for the training of huge CNNs.  Andrej Karpathy et. al. developed a deep neural network model for inferring hiding alignment between segments of sentences and the region of the image. They implemented a multimodal Recurrent Neural Network architecture that takes an input image and generates its description in text. They used CNN on the image side.

Konuşmacı: Fırat Kurt

Seminer Tarihi: 15 Nisan 2016

Seminer Veren Kurum: NETAŞ Ar-Ge 

Seminer Konusu: “eBilet Projesi, İş Zekası, Veri Ambarı, Veri Tabanı Yöneticiliği”

KonuşmacılarOsman Kumaş (Software Design Manager– Netaş Tanıtımı ve eBilet Projesi), Oğuz Kutlu (Sr. Solution Architect– Veri Tabanı Yöneticiliği), Fatih Gündoğdu (BI Architect – İş Zekası ve Veri Ambarı)

Seminer Tarihi: 14 Nisan 2016

Seminer Konusu: "Reinforcement learning in nonstationary environments using spatiotemporal analysis"

Seminer Özeti: Traditional reinforcement learning (RL) approaches fail to learn a policy to attain a dynamic or nonstationary goal. The reason for this is that the RL agent cannot start learning the changed environment from scratch once it has converged to a policy of the environment before the change. While heuristic solutions where the RL agent is encouraged to use least  recently attempted actions are successful for slowly changing environments (Sutton & Barto, 1998). They they do not form a sufficiently fast solution to follow a nonstationary goal state that moves with the same velocity of the RL agent. The problem of finding an nearoptimal policy for a stationary environment is well dealt with by classic RL algorithms such as the TD learning algorithm (Sutton, 1988), SARSA algorithm (Rummery & Niranjan, 1994) and the Q learning algorithm (Barto et al.,1989). These algorithms generally model the environment by a goal state which upon the visit of the agent generates a positive reinforcement and by states that connect the start state to the goal state.While classical RL algorithms provide satisfactory solutions for the stationary environment problem very well, they fail in nonstationary environments. Some attempts to solve this problem have been made such as the DG learning algorithm (Kaelbling, 1993) where the values are not a function of stateaction pairs but of a triplet of (s,a,g) where the goal is considered to be dynamic. In this presentation we will discuss a new approach to problem where there is an adversarial relation present between the dynamic goal and the RL agent. To tackle this the spatiotemporal information of the dynamic goal state is incorporated, in terms of stochastic processes, as the rewards of the RL agent into the environment model thus enabling a modular solution to the problem.

Konuşmacı: Burak Goncu

Seminer Tarihi: 14 Nisan 2016

Seminer Konusu: "Coreference Resolution Sieve Based on Answer Set Programming"

Seminer Özeti: Coreference resolution is the task of determining linguistic expressions that refer to the same real-world entity in natural language. Formally, coreference consists of two linguistic expressions antecedent and anaphor. The anaphor is the expression whose interpretation (i.e., associating it with an either concrete or abstract real-world entity) depends on that of the other expression. The antecedent is the linguistic expression on which an anaphor depends. Coreference resolution is important for natural language understanding tasks like summarization, question answering, and information extraction. The Sieve  technique is a recently introduced and successful coreference resolution method. Sieve architecture applies a battery of deterministic coreference models one at a time from highest to lowest precision, where each model builds on the previous model’s cluster output.  Answer Set Programming is a general purpose logic programming formalism that supports comfortable representation of knowledge, nonmonotonic reasoning processes, and reasoning with hybrid knowledge bases. In an ASP logic program we describe (i) a set of potential solutions, (ii) relationships between concepts in the solution, and (iii) constraints on solutions. The building blocks for programs are atoms, literals, and rules.

We envision (i) to create a theoretical framework and a practical implementation for the Sieve: an assumption-based Sieve based on Answer Set Programming, we plan (ii) to perform extensions to the Sieve by using existing linguistic knowledge bases and other natural language processing resources, (iii) to extensively evaluate the new approach on international benchmark corpora for the English language. We envision (i) to create a theoretical framework and a practical implementation for the Sieve: an assumption-based Sieve based on Answer Set Programming, we plan (ii) to perform extensions to the Sieve by using existing linguistic knowledge bases and other natural language processing resources, (iii) to extensively evaluate the new approach on international benchmark corpora for the English language.

Konuşmacı: Kenda Alakraa

Seminer Tarihi: 8 Nisan 2016

Seminer Veren Kurum: Huawei Ar-Ge 

Seminer Konusu: “Profiling User Interactions on Social Networks”

Konuşmacı: Dr. Cüneyt Gürcan Akçora, Huawei Research Turkey, Technology Introduction Lab

Seminer Tarihi: 24 Mart 2016

Seminer Konusu: "Evolutionary Computation for Dynamic Optimization Problems"

Seminer Özeti: Dynamic optimization problems (DOPs) have been rapidly attracting the interest of the research community, since most real world problems in different domains have various characteristics of dynamism. One or more underlying elements of a given dynamic optimization problem including the objective function, problem constraints, decision variables or environmental parameters may change over time, where the main motivation becomes tracking the global optimum value as close as possible. In this study, the characteristics of DOPs are presented briefly  which is followed by the details of selected DOPs.  A set of selected evolutionary techniques for solving DOP will be presented as part of the talk. Finally, performance evaluation of selected techniques on a case study will be presented.

Konuşmacı: Prof. Dr. Haluk Topcuoglu

Seminer Tarihi: 24 Mart 2016

Seminer Konusu: "Hierarchical Reinforcement Learning in Non-stationary Environments"

Seminer Özeti: A Reinforcement Learning (RL) agent mostly assumes environments are stationary which is not feasible on most real world problems. Most RL approaches adapt slow changes by forgetting the previous dynamics of the environment. A recent study on RL in non-stationary environments, Reinforcement Learning with Context Detection (RL-CD), presents a technique that helps determine changes of the environment's nature which the agent with the capability to learn different dynamics of the non-stationary environment. In this study we propose an autonomous agent that learns a dynamic environment by taking advantage of Hierarchical Reinforcement Learning (HRL) and present how the hierarchical structure can be integrated into RL-CD to speed up the convergence of a policy. We illustrate how our method outperforms RL-CD by employing hierarchies in RL.

Konuşmacı:  Doç. Dr. Borahan Tümer

Seminer Tarihi: 17 Mart 2016

Seminer Konusu: "Improving Efficiency in Database Marketing"

Seminer Özeti: The companies, particularly the banking industry, regularly mount campaigns to improve customer value by offering new products to existing customers. In recent years, this approach has gained significant momentum because of the increasing availability of customer data and the improved analysis capabilities in data mining. Typically, response models based on historical data are used to estimate the probability of a customer purchasing an additional product and the expected return from that additional purchase. Even with these computational improvements and accurate models of customer behavior, the problem of efficiently using marketing resources to maximize the return on marketing investment is a challenge. Simply knowing a customer’s probability of responding to a particular offer is not enough when a company has several products to promote and other business constraints to consider in its marketing planning. This problem is compounded because of the capability to launch multiple campaigns through several distribution channels over multiple time periods. The combination of alternatives creates a complicated array of possible actions.

Konuşmacı: Yrd. Doç. Mustafa Ağaoğlu

Seminer Tarihi: 17 Mart 2016

Seminer Konusu: "Auction And Barter Models For Electronic Markets"

Seminer Özeti: Recent advances in information technology have made major impact on markets and provided an ability to shift from the traditional physical markets where the traders meet at a certain place and at a certain time for exchanging commodities, to the electronic markets. However, in order for e-markets to be pervasive, innovative market mechanisms that support more complicated scenarios should be introduced. In this talk, two auction and barter based electronic market models will be introduced.

Our first model is a direct barter model for the course add/drop process in the universities. We model the course add/drop process as a direct barter problem in which add/drop requests can be placed as barter bids.

Our second model is the double auction with limited cover money model.

In this model, we propose the use of discrete time double auction institution for the trading of used goods as well as new ones. Our model allows declaration of an amount of cover money so that what is spent on purchased items minus the proceeds of sold items does not exceed this cover money amount. We also introduce a mechanism so that bidders may place multiple item requests in a single bid and limit the maximum number of items to be purchased.

Konuşmacı:Yrd. Doç. Ali Haydar Özer

Seminer Tarihi: 11 Mart 2016

Seminer Veren Kurumlar: MİTTO(Marmara Üniversitesi İnovasyon ve Teknoloji Transfer Ofisi), ANONİMYA, REKMOB,Lojika Fieldlabs

Seminer Konusu“Girişimcilik Destek Programları ve Örnek Başarı Hikayeleri”

Konuşmacılar: Mustafa Tüysüz(MİTTO), Münevver Olcaysoy(Uzman Danışman), Mustafa Burak Amasyalı(Lojika Fieldlabs), Taha Ali Çelik(ANONİMYA), Fatih Işık(REKMOB)

Seminer Tarihi: 10 Mart 2016

Seminer Konusu: "Modeling Variations First-Order Horn Abduction in Answer Set Programming using On-Demand Constraints and Flexible Value Invention "

Seminer Özeti: We study abduction in First Order Horn logic theories where all atoms can be abduced and we are looking for prefered solutions with respect to objective functions cardinality minimality, Coherence, or Weighted Abduction. We represent this reasoning problem in Answer Set Programming (ASP), in order to obtain a flexible framework for experimenting with global constraints andobjective functions, and to test the boundaries of what is possible with ASP, because realizing this problem in ASP is challenging as it requires value invention and equivalence between certain constants as the Unique Names Assumption does not hold in general. For permitting reasoning in cyclic theories, we formally describe fine-grained variations of limiting Skolemization. We evaluate ourencodings and extensions experimentally on the ACCEL benchmark for plan recognition in Natural Language Understanding. Our encodings are publicly available, modular, and our approach is more efficient than state-of-the-art solvers on the ACCEL benchmark. We identify term equivalence as a main instantiation bottleneck, and experiment with on-demand constraints that were used to elim- inate the same bottleneck in state-of-the-art solvers and make them applicable for larger datasets. Surprisingly, experiments show that this method is beneficial only for cardinality minimality with our ASP encodings.

Konuşmacı: Yrd. Doç. Dr. Peter Schueller

Seminer Tarihi: 10 Mart 2016

Seminer Konusu: "Incentive Mechanisms in User Provided Networks "

Seminer Özeti:  Increase in the number of mobile users demanding internet connectivity gave rise to a cooperative solution called User-provided connectivity (UPC) which is a promising paradigm to remedy internet connectivity needs of mobile users. In this model, participants cooperate to enable a group of mobile users to access internet while they have no or limited connectivity. One of the key research problems in UPC is giving incentives to mobile network subscribers to promote active participation. In this talk, several incentive mechanisms that are proposed recently will be overviewed. Next, a new scheme will be described for incentivizing users in a network assisted User Provided Network (UPN) in which subscribers with limited or no connectivity access Internet while still charging to their own quota. This scheme proposes a simple and applicable bargaining based mechanism to encourage mobile network subscribers to join the protocol to provide UPC. Since the scheme is network assisted network operators are expected to support and do not impose any restrictions on the protocol. In this scheme utility and cost functions are defined for participants in terms of provided throughput and battery energy, and the protocol operates iteratively as in the case of a real world bargaining.

Konuşmacı Yrd. Doç. Dr. Ömer Korçak

Seminer Tarihi: 4 Mart 2016

Seminer Veren Kurum: ACM

Seminer Konusu: “Yazılım Geliştirmede Etik”

Konuşmacı: Lemi Orhan ERGİN

Seminer Tarihi: 26 Şubat 2016

Seminer Veren Kurum: SAP Türkiye 

Seminer Konusu: “SAP ve ERP Uygulamaları”

Konuşmacı: İsmail Boz

Seminer Tarihi: 19 Şubat 2016

Seminer Konusu: “CSE497 ve CSE498 Bitirme Projesi Hazırlama Süreçleri”

Konuşmacılar: Yrd. Doç. Dr. Müjdat Soytürk, Öğr. Gör. Birol Gençyılmaz

Seminer Tarihi: 4 Aralık 2015

Seminer Veren Kurum: Migros Ar-Ge 

Seminer Konusu: “Perakende ve Teknoloji”

Konuşmacı: Kerim Tatlıcı,  Bilgi Teknolojileri & İş Geliştirme / Ar-Ge Merkezi Diretörü

Seminer Tarihi: 27 Kasım 2015

Seminer Veren Kurum: Türksat A.Ş.

Seminer Konusu: “Türksat Uygulamaları ve Ar-Ge Faaliyetleri”

Konuşmacı: Prof.Dr. Ensar Gül,  (Genel Müdür)   ve  Dr. Ahmet Savaş, (Yönetici, E-Devlet ve Bilgi Toplumu) 

Seminer Tarihi: 20 Kasım 2015

Seminer Veren Kurum: PAVOTEK

Seminer Konusu: M2M ve IoT Uygulamaları

Konuşmacı: Kutsal Anıl, Genel Müdür

Seminer Tarihi: 23 Ekim 2015 Cuma

Seminer Veren Kurum: Alcatel-Lucent AR-GE Departmanı

Seminer Konusu: "DSL Fixed Access and Internet(İsmail GÜN), Veritabanları ve SQL(Mehmet Caner UZUNKONAK )"

Konuşmacı: İsmail GÜN, Mehmet Caner UZUNKONAK 

Seminer Tarihi: 16 Ekim 2015 Cuma

Seminer Konusu: "Build Automation with Gradle(Build automation is an essential method to package and deploy the software. It also helps us to see what is going on before sending bugs to customer's hands. Gradle is a build automation tool which takes advantages of previous build automation tools and introduces a Groovy-based domain-specific language.)"

Konuşmacı: Çağlar Karabulut, Expert Software Engineer, ACM

Seminer Tarihi: 9 Ekim 2015 Cuma

Seminer Konusu: "Modeling “Reading between the Lines” Based on Scalable and Trainable Abduction and Large-scale Knowledge Acquisition"

Konuşmacı: Asst. Prof. Dr. Naoya Inoue from Tohoku University, Japan. http://www.cl.ecei.tohoku.ac.jp/



Seminer Tarihi: 8 Mayıs 2015

Seminer Konusu: "Akademik Poster Hazırlama"

Konuşmacı: Birol Gençyılmaz

Seminer Tarihi: 6 Mayıs 2015

Seminer Konusu: “Design Space Exploration for Customized Heterogeneous Multiprocessor System-on-Chip (MPSoC)”

Konuşmacı: Prof. Smail Niar

Seminer Tarihi: 17 Nisan 2015

Seminer Veren Kurum: Koç-Sistem

Seminer Konusu: “Bilgi Teknolojileri Servis Yönetimi”

Konusmaci: Dr. Turgay Karlıdere,  Koç Sistem Süreç, Hizmet ve Teknoloji Yönetimi – Grup Yöneticisi

Seminer Tarihi: 10 Nisan 2015

Seminer Veren Kurum: PAVOTEK

Seminer Konusu: “FPGA Uygulamaları” (Gömülü Sistemler ve Robotik)

Konusmaci: Kutsal Anıl,  Genel Müdür

Seminer Tarihi: 20 Mart 2015

Seminer Veren Kurum: Huawei Türkiye

Seminer Konusu: “Backward Design and Plan”

Konusmaci: Y.Müh. Ali Uçar, Yönetici, Huawei Türkiye

Seminer Tarihi: 13 Mart 2015

Seminer Veren Kurum: Huawei Türkiye Ar-Ge Merkezi

Seminer Konusu: “Intelligent Search and Deep Neural Language Models”

Konusmaci: Araştırma Mühendisi Çağlar Tırkaz

Seminer Tarihi: 6 Mart 2015 

Seminer Veren Kurum: ETİYA

Seminer konusu : M2M (Machine to Machine) Communication and IoT (Internet of Things)

Konuşmacılar: Dr. Ali Durmuş, ETİYA Genel Müdürü Rachmi Emir, ETİYA Iş Geliştirme Yöneticisi

Seminer Tarihi: 12 Aralık 2014

Seminer Veren Kurum: LKD ( Linux Kullanıcıları Derneği)

Seminer Konusu: "Özgür Yazılım ve Linux"

Konuşmacı: Mahir B. Aşut

Seminer Tarihi: 5 Aralık 2014

Seminer Veren Kurum: SUNUMO

Seminer Konusu: "Etkili Sunum Teknikleri"

Konuşmacı: Mehmet Ateş

Seminer Tarihi: 28 Kasım 2014

Seminer Veren Kurumlar: MİTTO(Marmara Üniversitesi İnovasyon ve Teknoloji Transfer Ofisi), KOSGEB(Küçük ve Orta Ölçekli İşletmeleri Geliştirme ve Destekleme Dairesi Başkanlığı), ANONİMYA, REKMOB

Seminer Konusu: "Ar-Ge Inovasyon Destek Programları ve Desteklerden Yararlanan Mezunlarımızın Şirketlerinden Örnekler"

Konuşmacılar: Gözde Canlı (MİTTO), Emre Akın (KOSGEB), Ziya Mahmutoğlu (ANONİMYA), Fatih Işık (REKMOB)

Seminer Tarihi: 21 Kasım 2014

Seminer Veren Kurum: ETİYA

Seminer Konusu: “Big Data, Application Areas and Technologies: An Overview”

Konuşmacı: Abdülkerim Mızrak

Seminer Tarihi: 7 Kasım 2014

Seminer Veren Kurum: BİLGEADAM

Seminer Konusu: "Search Engine Optimization and Mobile Marketing "

Konuşmacılar: Burhanettin Mirzooğlu, Özkan Yılmaz

Seminer Tarihi: 17 Ekim 2014

Seminer Veren Kurum: SONY

Seminer Konusu: "Guide for Evolving from Novices to Professional Software Developers"

Konuşmacı: Lemi Orhan Ergin

Seminer Tarihi: 10 Ekim 2014

Seminer Konusu: “Akademik Çalışmalarda Alıntı Yapma ve Meslek Etiği”

Konuşmacı: Birol Gençyılmaz

Bu sayfa Bilgisayar Mühendisliği tarafından en son 18.09.2017 15:40:41 tarihinde güncellenmiştir.