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Found 6 papers, 2 papers with code
Decoupling Decision-Making in Fraud Prevention through Classifier Calibration for Business Logic Action
Machine learning models typically focus on specific targets like creating classifiers, often based on known population feature distributions in a business context.
Improving Data Quality with Training Dynamics of Gradient Boosting Decision Trees
Real world datasets contain incorrectly labeled instances that hamper the performance of the model and, in particular, the ability to generalize out of distribution.
From Imitation to Prediction, Data Compression vs Recurrent Neural Networks for Natural Language Processing
In recent studies [1][13][12] Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions.
Generic LSH Families for the Angular Distance Based on Johnson-Lindenstrauss Projections and Feature Hashing LSH
In this paper we propose the creation of generic LSH families for the angular distance based on Johnson-Lindenstrauss projections.
Hash2Vec, Feature Hashing for Word Embeddings
In this paper we propose the application of feature hashing to create word embeddings for natural language processing.
Variations of the Similarity Function of TextRank for Automated Summarization
This article presents new alternatives to the similarity function for the TextRank algorithm for automatic summarization of texts.
