Now showing items 1-13 of 13

    • Active learning methods based on statistical leverage scores 

      Orhan, Cem (Bilkent University, 2016-08)
      In many real-world machine learning applications, unlabeled data are abundant whereas the class labels are expensive and/or scarce. An active learner aims to obtain a model with high accuracy with as few labeled instances ...
    • Çağrı merkezi metin madenciliği yaklaşımı 

      Yiğit, İ. O.; Ateş, A. F.; Güvercin, Mehmet; Ferhatosmanoğlu, Hakan; Gedik, Buğra (IEEE, 2017-05)
      Günümüzde çağrı merkezlerindeki görüşme kayıtlarının sesten metne dönüştürülebilmesi görüşme kaydı metinleri üzerinde metin madenciliği yöntemlerinin uygulanmasını mümkün kılmaktadır. Bu çalışma kapsamında görüşme ...
    • Detecting Falls with Wearable Sensors Using Machine Learning Techniques 

      Ozdemir, A. T.; Barshan, B. (MDPI, 2014-06-18)
      Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects' body at six ...
    • Example based machine translation with type associated translation examples 

      Doğan, Hande (Bilkent University, 2007)
      Example based machine translation is a translation technique that leans on machine learning paradigm. This technique had been modeled by the learning process as: a man is given short and simple sentences in language A ...
    • Fog supported wireless sensor networks for forest fire detection 

      Amira, Fouad (Bilkent University, 2018-09)
      Fog computing is a new paradigm that aims to extend the concept of cloud computing to the edge of the network, providing the end users network with extra storage and processing power. One big contribution of Fog computing ...
    • Instance-based regression by partitioning feature projections 

      Uysal, İ.; Güvenir, H. A. (Springer, 2004)
      A new instance-based learning method is presented for regression problems with high-dimensional data. As an instance-based approach, the conventional method, KNN, is very popular for classification. Although KNN performs ...
    • Learning differential diagnosis of erythemato-squamous diseases using voting feature intervals 

      Güvenir, H. A.; Demiröz, G.; İlter, N. (Elsevier, 1998)
      A new classification algorithm, called VFI5 (for Voting Feature Intervals), is developed and applied to problem of differential diagnosis of erythemato-squamous diseases. The domain contains records of patients with known ...
    • Learning translation templates from examples 

      Güvenır, H. A.; Cıceklı, I. (Elsevier, 1998)
      This paper proposes a mechanism for learning lexical level correspondences between two languages from a set of translated sentence pairs. The proposed mechanism is based on an analogical reasoning between two translation ...
    • A learning-based schedulıng system wıth continuous control and update structure 

      Metan, Gökhan (Bilkent University, 2005)
      In today’s highly competitive business environment, the product varieties of firms tend to increase and the demand patterns of commodities change rapidly. Especially for high tech industries, the product life cycles ...
    • Mathematical Model of Causal Inference in Social Networks 

      Simsek, M.; Delibalta, I.; Baruh, L.; Kozat, S. S. (Institute of Electrical and Electronics Engineers Inc., 2016)
      In this article, we model the effects of machine learning algorithms on different Social Network users by using a causal inference framework, making estimation about the underlying system and design systems to control ...
    • Multiplication free neural networks 

      Mallah, Maen M. A. (Bilkent University, 2018-01)
      Artificial Neural Networks, commonly known as Neural Networks (NNs), have become popular in the last decade for their achievable accuracies due to their ability to generalize and respond to unexpected patterns. In general, ...
    • Numbers in politics : comparative quantitative analysis & modeling in foreign policy orientation and election forecasting 

      Taylan, Enes (Bilkent University, 2017-05)
      To advance social science in the direction of accurate and reliable quantitative models, especially in the fields of International Relations and Political Science, new novel methodologies borrowed from the Computer Science ...
    • Using multiple sources of information for constraint-based morphological disambiguation 

      Tür, Gökhan (Bilkent University, 1996)
      This thesis presents a constraint-based morphological disambiguation approach that is applicable to languages with complex morphology-specifically agglutiriiitive languages with productive inflectional and derivational ...