The document discusses hyperparameter optimization in machine learning models. It introduces various hyperparameters that can affect model performance, and notes that as models become more complex, the number of hyperparameters increases, making manual tuning difficult. It formulates hyperparameter optimization as a black-box optimization problem to minimize validation loss and discusses challenges like high function evaluation costs and lack of gradient information.
Dependent Types and Dynamics of Natural LanguageDaisuke BEKKI
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The document discusses dependent types and dynamics in natural language semantics. It provides an overview of Dependent Type Semantics (DTS), which takes a proof-theoretic approach to semantics. DTS uses dependent types to provide a unified analysis of inferences and anaphora resolution. The document explains how DTS handles various phenomena involving anaphora and dynamic semantics, such as E-type anaphora and donkey anaphora, through the use of underspecified terms and type checking.
First part shows several methods to sample points from arbitrary distributions. Second part shows application to population genetics to infer population size and divergence time using obtained sequence data.
The document discusses hyperparameter optimization in machine learning models. It introduces various hyperparameters that can affect model performance, and notes that as models become more complex, the number of hyperparameters increases, making manual tuning difficult. It formulates hyperparameter optimization as a black-box optimization problem to minimize validation loss and discusses challenges like high function evaluation costs and lack of gradient information.
Dependent Types and Dynamics of Natural LanguageDaisuke BEKKI
?
The document discusses dependent types and dynamics in natural language semantics. It provides an overview of Dependent Type Semantics (DTS), which takes a proof-theoretic approach to semantics. DTS uses dependent types to provide a unified analysis of inferences and anaphora resolution. The document explains how DTS handles various phenomena involving anaphora and dynamic semantics, such as E-type anaphora and donkey anaphora, through the use of underspecified terms and type checking.
First part shows several methods to sample points from arbitrary distributions. Second part shows application to population genetics to infer population size and divergence time using obtained sequence data.