L1 регуляризация

This paper presents a comparative study of five parameter estimation algorithms on four NLP tasks. Three of the five algorithms are well-known in the computational linguistics community: Maximum Entropy (ME) …...

We use L1 regularized transductive regres- sion to learn mappings between source and target features of the training sets derived for each test sentence and use these mappings to rerank …...

AbstractLong Short-Term Memory recurrent neural network (LSTM) is widely used and known to capture informative long-term syntactic dependencies. However, how such information are reflected in its internal vectors for natural …...

AbstractThe input vocabulary and the representations learned are crucial to the performance of neural NLP models. Using the full vocabulary results in less explainable and more memory intensive models, with …...