Browsing by Keywords "State of the art"
Now showing items 1-6 of 6
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Adaptive hierarchical space partitioning for online classification
(IEEE, 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
(IEEE, 2017-10)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
(IEEE, 2015-06)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
(IEEE, 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
(IEEE, 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
(IEEE, 2017-10)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 ...
