Diversified Bayesian Nonnegative Matrix Factorization Article Swipe
Maoying Qiao
,
Jun Yu
,
Tongliang Liu
,
Xinchao Wang
,
Dacheng Tao
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v34i04.5991
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v34i04.5991
Nonnegative matrix factorization (NMF) has been widely employed in a variety of scenarios due to its capability of inducing semantic part-based representation. However, because of the non-convexity of its objective, the factorization is generally not unique and may inaccurately discover intrinsic “parts” from the data. In this paper, we approach this issue using a Bayesian framework. We propose to assign a diversity prior to the parts of the factorization to induce correctness based on the assumption that useful parts should be distinct and thus well-spread. A Bayesian framework including this diversity prior is then established. This framework aims at inducing factorizations embracing both good data fitness from maximizing likelihood and large separability from the diversity prior. Specifically, the diversity prior is formulated with determinantal point processes (DPP) and is seamlessly embedded into a Bayesian NMF framework. To carry out the inference, a Monte Carlo Markov Chain (MCMC) based procedure is derived. Experiments conducted on a synthetic dataset and a real-world MULAN dataset for multi-label learning (MLL) task demonstrate the superiority of the proposed method.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaai.v34i04.5991
- https://ojs.aaai.org/index.php/AAAI/article/download/5991/5847
- OA Status
- diamond
- Cited By
- 3
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2997007367
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https://openalex.org/W2997007367Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1609/aaai.v34i04.5991Digital Object Identifier
- Title
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Diversified Bayesian Nonnegative Matrix FactorizationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
-
2020-04-03Full publication date if available
- Authors
-
Maoying Qiao, Jun Yu, Tongliang Liu, Xinchao Wang, Dacheng TaoList of authors in order
- Landing page
-
https://doi.org/10.1609/aaai.v34i04.5991Publisher landing page
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https://ojs.aaai.org/index.php/AAAI/article/download/5991/5847Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://ojs.aaai.org/index.php/AAAI/article/download/5991/5847Direct OA link when available
- Concepts
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Computer science, Non-negative matrix factorization, Bayesian probability, Markov chain Monte Carlo, Matrix decomposition, Artificial intelligence, Bayesian inference, Inference, Correctness, Machine learning, Variety (cybernetics), Algorithm, Eigenvalues and eigenvectors, Quantum mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
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2023: 2, 2021: 1Per-year citation counts (last 5 years)
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30Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2032345535, https://openalex.org/W2120408219, https://openalex.org/W178113997, https://openalex.org/W1882879704, https://openalex.org/W1893900968, https://openalex.org/W2912497862, https://openalex.org/W2973519034, https://openalex.org/W2138779671, https://openalex.org/W1902027874, https://openalex.org/W6680012447, https://openalex.org/W2136171036, https://openalex.org/W6718044918, https://openalex.org/W1675155851, https://openalex.org/W2105431676, https://openalex.org/W1841002610, https://openalex.org/W1979301943, https://openalex.org/W2904398352, https://openalex.org/W2605809234, https://openalex.org/W2776922857, https://openalex.org/W2904551296, https://openalex.org/W2410641892, https://openalex.org/W2023714745, https://openalex.org/W2435477720, https://openalex.org/W2140318696, https://openalex.org/W2135029798, https://openalex.org/W4288616989, https://openalex.org/W2914578055, https://openalex.org/W2952397387, https://openalex.org/W2951813019, https://openalex.org/W3014978418 |
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