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Video in druga učna gradiva
Oznake: computer science;machine learning;bayesian learning
Statistical and computational concerns have motivated parameter estimators based on various forms of likelihood, e.g., joint, conditional, and pseudolikelihood. In this paper, we present a unified framework for studying these estimators, which allows us to compare their relative (statistical) effici ...
Leto: 2008 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning;natural language processing
Structured models often achieve excellent performance but can be slow at test time. We investigate structure compilation, where we replace structure with features, which are often computationally simpler but unfortunately statistically more complex. We analyze this tradeoff theoretically and empiric ...
Leto: 2008 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning
Spectral methods are satisfying in that they provide statistically consistent estimators. However, two issues still challenge their widespread adoption: they tend to be inaccurate in smaller data regimes, and they do not directly apply to richer classes of latent-variable models. In this talk, we sh ...
Leto: 2013 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning
Building systems that can understand human language—being able to answer questions, follow instructions, carry on dialogues—has been a long-standing challenge since the early days of AI. Due to recent advances in machine learning, there is again renewed interest in taking on this formidable task. A ...
Leto: 2015 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning
Leto: 2009 Vir: videolectures.net
Št. zadetkov: 5
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