Search Results for "lr"

...Poly learning rate, where the learning rate is scaled down linearly from the starting value down to zero during training. Considered as the go-to scheduler for semantic segmentation. One Cycle learning rate, for a learning rate LR, we start from LR / 10 up to LR for 30% of the training time, and we scale down to LR / 25 for remaining time, the scaling is done in a cos annealing fashion (see Figure bellow), the momentum is also modified but in the opposite manner starting from 0.95 down to 0.85 and up to 0.95.

xLearn is a high-performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM), all of which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data. Many real-world datasets deal with high dimensional sparse feature vectors like a recommendation system where the number of categories and users is on the order of millions. ...

The name stands for ensemble learning framework. It is a collection of machine learning algorithms for classification and regression with the possibility of connecting them together via ensemble learning. It is written in C++.

lightJacc is a small but strong grammar parser generator. It adopts a parsing strategy of its own: dynamic concurrent parsing -- which made it much stronger than LR or LL family CCs (YACC, ANTLR, etc), but still keep good performance.