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In latent learning, one changes behavior only when there is sufficient motivation later than when they subconsciously retained the information. [1] Latent learning is when the observation of something, rather than experiencing something directly, can affect later behavior. Observational learning can be many things. A human observes a behavior ...
Việt-nam bách-khoa từ-điển (Encyclopedia of Vietnam), a set of encyclopedias with annotations in Chinese, English and French by Đào Đăng Vỹ, a Vietnamese scholar; published from 1959 to 1963 in Saigon, Republic of Vietnam. [3] [4]
Từ điển bách khoa Việt Nam (lit: Encyclopaedic Dictionary of Vietnam) is a state-sponsored Vietnamese-language encyclopedia that was first published in 1995. It has four volumes consisting of 40,000 entries, the final of which was published in 2005. [1] The encyclopedia was republished in 2011.
Pages for logged out editors learn more. Contributions; Talk; Từ điển bách khoa toàn thư Việt Nam
The Vietnamese Wikipedia initially went online in November 2002, with a front page and an article about the Internet Society.The project received little attention and did not begin to receive significant contributions until it was "restarted" in October 2003 [3] and the newer, Unicode-capable MediaWiki software was installed soon after.
Đồng Thị Bích Thuỷ was born on 10 December 1954 in Phú Vang district, in the Thừa Thiên Huế province of Vietnam. She graduated in business administration from the University of Lausanne in Switzerland in 1975 and obtained a PhD in management informatics from the University of Geneva in Switzerland in 1986, defending a thesis on information systems and financial informatics databases.
Vienna (Viên in Vietnamese) is the only city whose name in Vietnamese is borrowed from French [citation needed]. Hong Kong and Macau names are borrowed from English by direct transliteration into Hồng Kông and Ma Cao instead of Hương Cảng and Áo Môn in Sino-Vietnamese pronunciation.
When LDA machine learning is employed, both sets of probabilities are computed during the training phase, using Bayesian methods and an Expectation Maximization algorithm. LDA is a generalization of older approach of probabilistic latent semantic analysis (pLSA), The pLSA model is equivalent to LDA under a uniform Dirichlet prior distribution.