Results 1 to 10 of about 70 (69)
Learning Term Discrimination [PDF]
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020 Document indexing is a key component for efficient information retrieval (IR). After preprocessing steps such as stemming and stop-word removal, document indexes usually store term-frequencies (tf). Along with tf (that only reflects the importance of a term in a document), traditional IR models use term discrimination values (TDVs) such as inverse ...
Jibril Frej +3 more
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Discriminately decreasing discriminability with learned image filters [PDF]
2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012 In machine learning and computer vision, input images are often filtered to increase data discriminability. In some situations, however, one may wish to purposely decrease discriminability of one classification task (a "distractor" task), while simultaneously preserving information relevant to another (the task-of-interest): For example, it may be ...
Jacob Whitehill, Javier R. Movellan
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Discriminative learning of apparel features [PDF]
2015 14th IAPR International Conference on Machine Vision Applications (MVA), 2015 Fashion is a major segment in e-commerce with growing importance and a steadily increasing number of products. Since manual annotation of apparel items is very tedious, the product databases need to be organized automatically, e.g. by image classification.
Rothe, Rasmus +3 more
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Discriminative Active Learning
CoRR, 2019 11 pages, 3 ...
Daniel Gissin, Shai Shalev-Shwartz
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Symmetry and discrimination learning
Acta Psychologica, 1974 Abstract A hypothesis that the difficulties which subjects encounter whilst engaged in a traditional discrimination learning task may be seen as influenced by symmetry of individual stimuli as well as of arrangements of stimuli was examined. The data obtained as well as published data are interpreted as suggesting that the nature of symmetry of an ...
J B, Deregowski, D, Ellis
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Probably almost discriminative learning [PDF]
Machine Learning, 1992 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Journal of Advanced Computational Intelligence and Intelligent Informatics, 2004 This paper presents MCE/GPD using GPD that is known as a highly effective discriminative learning method. MCE/GPD is an excellent recognition method that is applicable especially to speech recognition, since it excels in recognizing performance and can be used to deal with variable-length vectors.
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Learning to discriminate face view
Journal of Vision, 2010 Although perceptual learning of simple visual features has been studied extensively and intensively for many years, we still know little about the mechanisms of perceptual learning of complex object recognition. In a series of seven experiments, human perceptual learning in discrimination of in-depth orientation of face view was studied using ...
Taiyong, Bi +4 more
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Learning complex texture discrimination
Journal of the Optical Society of America A, 2018 Higher-order spatial correlations contribute strongly to visual structure and salience, and are common in the natural environment. One method for studying this structure has been through the use of highly controlled texture patterns whose obvious structure is defined entirely by third- and higher-order correlations.
T. Maddess +5 more
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Learning to Write with Cooperative Discriminators [PDF]
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018 Recurrent Neural Networks (RNNs) are powerful autoregressive sequence models, but when used to generate natural language their output tends to be overly generic, repetitive, and self-contradictory. We postulate that the objective function optimized by RNN language models, which amounts to the overall perplexity of a text, is not expressive enough to ...
Ari Holtzman +5 more
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