On the Practicality of Local Ranking-Based Cancelable Iris Recognition
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3089078
Abstract: Practical cancelable biometrics (CB) schemes should satisfy the requirements of revocability, non-invertibility, and non-linkability without deteriorating the matching accuracy of the underlying biometric recognition system. In order to bridge the gap between theory and practice,… read more here.
Keywords: accuracy; local ranking; ranking based; attack ... See more keywords
Collaborative Filtering With Ranking-Based Priors on Unknown Ratings
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DOI: 10.1109/mis.2020.3000012
Abstract: Advanced collaborative filtering methods based on explicit feedback assume that unknown ratings are missing not at random. The state-of-the-art algorithm hypothesizes that unknown items are weakly rated and sets an explicit prior to unknown ratings.… read more here.
Keywords: ranking based; unknown items; filtering ranking; collaborative filtering ... See more keywords
Ranking-Based Locality Sensitive Hashing-Enabled Cancelable Biometrics: Index-of-Max Hashing
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2017.2753172
Abstract: In this paper, we propose a ranking-based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed “Index-of-Max” (IoM) hashing for biometric template protection. With externally generated random parameters, IoM hashing transforms a real-valued biometric feature vector… read more here.
Keywords: ranking based; index max; biometrics; iom hashing ... See more keywords
Ranking-Based Implicit Regularization for One-Class Collaborative Filtering
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2021.3069057
Abstract: One-class collaborative filtering (OCCF) problems are ubiquitous in real-world recommendation systems, such as news recommendation, but suffer from data sparsity and lack of negative items. To address the challenge, the state-of-the-art algorithm assigns uninteracted items… read more here.
Keywords: uninteracted items; one class; collaborative filtering; based implicit ... See more keywords
inFRank: a ranking-based identification of influential genes in biological networks
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DOI: 10.18632/oncotarget.11878
Abstract: Capturing the predominant driver genes is critical in the analysis of high-throughput experimental data; however, existing methods scarcely include the unique characters of biological networks. Herein we introduced a ranking-based computational framework (inFRank) to rank… read more here.
Keywords: ranking based; biological networks; identification influential; infrank ranking ... See more keywords