Latent Space

A Latent Space is a measurable space that ...

• Context:
  • It can range from being a Continuous Latent Space to being a Discrete Latent Space.
• See: Latent Factor Modeling, Latent Variable.

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References

2012

• (Guo & Diab, 2012) ⇒ Weiwei Guo, and Mona Diab. (2012). “Modeling Sentences in the Latent Space.” In: Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers (ACL 2012).
  • QUOTE: … Latent variable models, such as Latent Semantic Analysis (LSA) (Landauer et al., 1998), Probabilistic Latent Semantic Analysis (PLSA) (Hofmann, 1999), Latent Dirichlet Allocation (LDA) (Blei et al., 2003) can solve the two issues naturally by modeling the semantics of words and sentences simultaneously in the low-dimensional latent space. However, attempts at addressing SS using LSA perform significantly below high dimensional word similarity based models (Mihalcea et al., 2006; O’Shea et al., 2008).

2004

• (Monay & Perez, 2004) ⇒ Florent Monay, and Daniel Gatica-Perez. (2004). “PLSA-based Image Auto-annotation: Constraining the Latent Space.” In: Proceedings of the 12th annual ACM International Conference on Multimedia, pp. 348-351 . ACM,
  • QUOTE: … When this ambiguities occur, a disambiguate latent space representation could potentially be extracted from the data, which is the goal of PLSA

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