Now showing items 1-6 of 6

    • Adaptive Hierarchical Space Partitioning for Online Classification 

      Fatih Kilic, O.; Denizcan Vanli, N.; Ozkan, H.; Delibalta, I.; Kozat, S. S. (European Signal Processing Conference, EUSIPCO, 2016)
      We propose an online algorithm for supervised learning with strong performance guarantees under the empirical zero-one loss. The proposed method adaptively partitions the feature space in a hierarchical manner and generates ...
    • Attributes2Classname: a discriminative model for attribute-based unsupervised zero-shot learning 

      Demirel, B.; Cinbis, R. G.; Ikizler-Cinbis, N. (Institute of Electrical and Electronics Engineers Inc., 2017)
      We propose a novel approach for unsupervised zero-shot learning (ZSL) of classes based on their names. Most existing unsupervised ZSL methods aim to learn a model for directly comparing image features and class names. ...
    • FAME: Face Association through Model Evolution 

      Golge, E.; Duygulu P. (IEEE Computer Society, 2014)
      We attack the problem of building classifiers for public faces from web images collected through querying a name. The search results are very noisy even after face detection, with several irrelevant faces corresponding to ...
    • Signal denoising by piecewise continuous polynomial fitting 

      Yildiz, A.; Arikan, O. (2010)
      Piecewise smooth signal denoising is cast as a non-linear optimization problem in terms of transition boundaries and a parametric smooth signal family. Optimal transition boundaries for a given number of transitions are ...
    • An upper bound on the capacity of non-binary deletion channels 

      Rahmati, M.; Duman, T.M. (2013)
      We derive an upper bound on the capacity of non-binary deletion channels. Although binary deletion channels have received significant attention over the years, and many upper and lower bounds on their capacity have been ...
    • Visual transformation aided contrastive learning for video-based kinship verification 

      Dibeklioglu, H. (Institute of Electrical and Electronics Engineers Inc., 2017)
      Automatic kinship verification from facial information is a relatively new and open research problem in computer vision. This paper explores the possibility of learning an efficient facial representation for video-based ...