1,024 research outputs found
Scalarizing Functions in Bayesian Multiobjective Optimization
Scalarizing functions have been widely used to convert a multiobjective
optimization problem into a single objective optimization problem. However,
their use in solving (computationally) expensive multi- and many-objective
optimization problems in Bayesian multiobjective optimization is scarce.
Scalarizing functions can play a crucial role on the quality and number of
evaluations required when doing the optimization. In this article, we study and
review 15 different scalarizing functions in the framework of Bayesian
multiobjective optimization and build Gaussian process models (as surrogates,
metamodels or emulators) on them. We use expected improvement as infill
criterion (or acquisition function) to update the models. In particular, we
compare different scalarizing functions and analyze their performance on
several benchmark problems with different number of objectives to be optimized.
The review and experiments on different functions provide useful insights when
using and selecting a scalarizing function when using a Bayesian multiobjective
optimization method
Effects of Gamification on Speed and Accuracy on an Interdependent Paper Sorting Task
This study examined the effects of gamification, i.e. (what makes games challenging, engaging and fun), and its effects on speed and accuracy on an interdependent paper sorting task. Undergraduate students (N=42) at the University of Central Florida participated by working interdependently in groups to sort numbered pieces of paper into piles before and after either playing video games or doing back-to-back drawing(basic team building exercises). It was hypothesized that participants who played video games would sort pieces of paper into the piles faster and more accurate than those who did back-to-back team exercises. Results showed that playing video games was not better than doing basic team exercises, but that the two tasks were relatively equal. Although groups were formed and dissolved quickly, there was improvement between the pre and posttests. While the experiment did not yield significant results, it is possible that using different video games or different interdependent tasks could foster increases in speed and accuracy compared to back-to-back drawing
Other People Think
What is “Making Good Trouble?” Well, for Meredith, it’s doing little things that you’re “not supposed to do” but aren’t wrong either. It’s taking every paint sample in the hardware store, carrying around a rubber dinosaur with you everywhere you go, having rainbow jell-o for breakfast, etc. “Making good trouble” is sticking up for what you believe in. For Meredith, that means advocating to save the US Postal Service and challenging what fine art in academia is. Making good trouble means sticking up for others, no matter what ethnicity, gender, sexuality, age, religion, or economic status a person has
Rainbows in my Head
What is “Making Good Trouble?” Well, for Meredith, it’s doing little things that you’re “not supposed to do” but aren’t wrong either. It’s taking every paint sample in the hardware store, carrying around a rubber dinosaur with you everywhere you go, having rainbow jell-o for breakfast, etc. “Making good trouble” is sticking up for what you believe in. For Meredith, that means advocating to save the US Postal Service and challenging what fine art in academia is. Making good trouble means sticking up for others, no matter what ethnicity, gender, sexuality, age, religion, or economic status a person has
The life and demography of the side-blotched lizard, Uta stansburiana.
http://deepblue.lib.umich.edu/bitstream/2027.42/56376/1/MP132.pd
Population Structure And Effective Size Of A Lizard Population
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137629/1/evo03334.pd
MDOCS Flyer-2015-01-01, MYORS (Make Your Own Radio Show) with Adam Tinkle
Adam Tinkle hosts MYORS Make Your Own Radio Show, a once-a-month session to help Skidmore and Saratoga Springs community members create their own audio work using everyday tools and widely availble programs
Neural Network With Nlp
This thesis is about neural networks and how their algorithmic systems work. Neural networks are well-suited to aiding people with complex challenges in real-world situations. Thesis topics include nonlinear and complicated interactions between inputs and outputs, as well as making inferences, discovering hidden links, patterns, and predictions, and modeling highly volatile data and variations to forecast uncommon events. Neural networks have the potential to help people make better decisions. NLP is a technique for analyzing, interpreting, and comprehending large amounts of text. We can no longer evaluate the text using traditional approaches due to the massive volumes of text data and the exceedingly unstructured data source, which is where NLP comes in. As a result, the research focuses on what a neural network is and how different types of neural networks are used in natural language processing. NLP (natural language processing) is a method for analyzing, interpreting, and comprehending vast amounts of text. Due to the huge volumes of text data and the extremely unstructured data source, we can no longer analyze the text using standard approaches, which is where NLP comes in. As a result, the study concentrates on what a neural network is and how various types of neural networks are used in natural language processing. Due to their exceptional success in numerous NLP tasks, BERT in particular has gotten a lot of attention. Google\u27s Bidirectional Encoder Representations from Transformers (BERT) is a Transformer-based machine learning methodology for pre-training in natural language processing (NLP)
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