FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3004100023> ?p ?o ?g. }

• W3004100023 abstract "Exact recovery of tensor decomposition (TD) methods is a desirable property in both unsupervised learning and scientific data analysis. The numerical defects of TD methods, however, limit their practical applications on real-world data. As an alternative, convex tensor decomposition (CTD) was proposed to alleviate these problems, but its exact-recovery property is not properly addressed so far. To this end, we focus on latent convex tensor decomposition (LCTD), a practically widely-used CTD model, and rigorously prove a sufficient condition for its exact-recovery property. Furthermore, we show that such property can be also achieved by a more general model than LCTD. In the new model, we generalize the classic tensor (un-)folding into reshuffling operation, a more flexible mapping to relocate the entries of the matrix into a tensor. Armed with the reshuffling operations and exact-recovery property, we explore a totally novel application for (generalized) LCTD, i.e., image steganography. Experimental results on synthetic data validate our theory, and results on image steganography show that our method outperforms the state-of-the-art methods." @default.
• W3004100023 created "2020-02-07" @default.
• W3004100023 creator A5003753200 @default.
• W3004100023 creator A5007098537 @default.
• W3004100023 creator A5016846734 @default.
• W3004100023 creator A5043262479 @default.
• W3004100023 creator A5047240103 @default.
• W3004100023 creator A5053565482 @default.
• W3004100023 creator A5083182987 @default.
• W3004100023 date "2018-05-22" @default.
• W3004100023 modified "2023-09-23" @default.
• W3004100023 title "Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition under Reshuffling" @default.
• W3004100023 cites W1246381107 @default.
• W3004100023 cites W1521672915 @default.
• W3004100023 cites W1548802052 @default.
• W3004100023 cites W1638985343 @default.
• W3004100023 cites W1736339626 @default.
• W3004100023 cites W1966096622 @default.
• W3004100023 cites W1983576072 @default.
• W3004100023 cites W1993482030 @default.
• W3004100023 cites W2000045479 @default.
• W3004100023 cites W2024165284 @default.
• W3004100023 cites W2025328853 @default.
• W3004100023 cites W2025603201 @default.
• W3004100023 cites W2047643928 @default.
• W3004100023 cites W2050363513 @default.
• W3004100023 cites W2103972604 @default.
• W3004100023 cites W2125124498 @default.
• W3004100023 cites W2159023782 @default.
• W3004100023 cites W2170598445 @default.
• W3004100023 cites W2431890537 @default.
• W3004100023 cites W2549362047 @default.
• W3004100023 cites W2611328865 @default.
• W3004100023 cites W2615181921 @default.
• W3004100023 cites W2739547565 @default.
• W3004100023 cites W2745024368 @default.
• W3004100023 cites W2768368415 @default.
• W3004100023 cites W2771036112 @default.
• W3004100023 cites W2923380536 @default.
• W3004100023 cites W2934600951 @default.
• W3004100023 cites W2936840939 @default.
• W3004100023 cites W2950196489 @default.
• W3004100023 cites W2950706335 @default.
• W3004100023 cites W2951881727 @default.
• W3004100023 cites W2952543272 @default.
• W3004100023 cites W2962881496 @default.
• W3004100023 cites W2963614475 @default.
• W3004100023 cites W2982317909 @default.
• W3004100023 cites W3104624268 @default.
• W3004100023 doi "https://doi.org/10.48550/arxiv.1805.08465" @default.
• W3004100023 hasPublicationYear "2018" @default.
• W3004100023 type Work @default.
• W3004100023 sameAs 3004100023 @default.
• W3004100023 citedByCount "1" @default.
• W3004100023 countsByYear W30041000232019 @default.
• W3004100023 crossrefType "posted-content" @default.
• W3004100023 hasAuthorship W3004100023A5003753200 @default.
• W3004100023 hasAuthorship W3004100023A5007098537 @default.
• W3004100023 hasAuthorship W3004100023A5016846734 @default.
• W3004100023 hasAuthorship W3004100023A5043262479 @default.
• W3004100023 hasAuthorship W3004100023A5047240103 @default.
• W3004100023 hasAuthorship W3004100023A5053565482 @default.
• W3004100023 hasAuthorship W3004100023A5083182987 @default.
• W3004100023 hasBestOaLocation W30041000231 @default.
• W3004100023 hasConcept C106487976 @default.
• W3004100023 hasConcept C111472728 @default.
• W3004100023 hasConcept C112680207 @default.
• W3004100023 hasConcept C11413529 @default.
• W3004100023 hasConcept C120665830 @default.
• W3004100023 hasConcept C121332964 @default.
• W3004100023 hasConcept C124681953 @default.
• W3004100023 hasConcept C126255220 @default.
• W3004100023 hasConcept C134306372 @default.
• W3004100023 hasConcept C138885662 @default.
• W3004100023 hasConcept C151201525 @default.
• W3004100023 hasConcept C155281189 @default.
• W3004100023 hasConcept C158693339 @default.
• W3004100023 hasConcept C159985019 @default.
• W3004100023 hasConcept C18903297 @default.
• W3004100023 hasConcept C189950617 @default.
• W3004100023 hasConcept C192209626 @default.
• W3004100023 hasConcept C192562407 @default.
• W3004100023 hasConcept C202444582 @default.
• W3004100023 hasConcept C2524010 @default.
• W3004100023 hasConcept C28826006 @default.
• W3004100023 hasConcept C33923547 @default.
• W3004100023 hasConcept C41008148 @default.
• W3004100023 hasConcept C42355184 @default.
• W3004100023 hasConcept C520416788 @default.
• W3004100023 hasConcept C62520636 @default.
• W3004100023 hasConcept C80444323 @default.
• W3004100023 hasConcept C86803240 @default.
• W3004100023 hasConceptScore W3004100023C106487976 @default.
• W3004100023 hasConceptScore W3004100023C111472728 @default.
• W3004100023 hasConceptScore W3004100023C112680207 @default.
• W3004100023 hasConceptScore W3004100023C11413529 @default.
• W3004100023 hasConceptScore W3004100023C120665830 @default.
• W3004100023 hasConceptScore W3004100023C121332964 @default.
• W3004100023 hasConceptScore W3004100023C124681953 @default.
• W3004100023 hasConceptScore W3004100023C126255220 @default.

• next