Essays about: "sparse group lasso"
Found 5 essays containing the words sparse group lasso.
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1. Machine Learning Prediction of Enzymes’ Optimal Catalytic Temperatures
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Enzymes that have been genetically engineered to withstand high temperatures are used by industry to make products with less waste and pollution. Different features of protein structure affect the optimal catalytic temperature ("topt") at which enzymes catalyze reactions most efficiently. READ MORE
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2. Nowcasting U.S. inflation using mixed frequency real-time data
University essay from Lunds universitet/Matematisk statistikAbstract : Different models were developed with the aim of nowcasting inflation at a daily basis with high frequency variables, while using real-time data to avoid look ahead bias. Both popular machine learning models such as Random Forest and XGBoost, and more traditional models such as UMIDAS and Almon distributed lag models were used to make the nowcasts. READ MORE
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3. Identifying Content Blocks on Web Pages using Recursive Neural Networks and DOM-tree Features
University essay from Linköpings universitet/Interaktiva och kognitiva systemAbstract : The internet is a source of abundant information spread across different web pages. The identification and extraction of information from the internet has long been an active area of research for multiple purposes relating to both research and business intelligence. READ MORE
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4. Prospect Utility Portfolio Optimization
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : Portfolio choice theory have in the last decades seen a rise in utilising more advanced utility functions for finding optimal portfolios. This is partly a consequence of the relatively simplistic nature of the quadratic utility, which is often assumed in the classical mean-variance framework. READ MORE
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5. A Parametric Method for Multi-Pitch Estimation
University essay from Lunds universitet/Matematisk statistikAbstract : This thesis proposes a novel method for multi-pitch estimation. The method operates by posing pitch estimation as a sparse recovery problem which is solved using convex optimization techniques. In that respect, it is an extension of an earlier presented estimation method based on the group-LASSO. READ MORE