WebApr 7, 2024 · Inspired by label smoothing and driven by the ambiguity of boundary annotation in NER engineering, we propose boundary smoothing as a regularization technique for span-based neural NER models. It re-assigns entity probabilities from annotated spans to the surrounding ones. WebMay 20, 2024 · Label Smoothing Regularization (LSR) is a widely used tool to generalize classification models by replacing the one-hot ground truth with smoothed labels. Recent research on LSR has increasingly ...
[2006.11653] Towards Understanding Label Smoothing
WebRegularization helps to improve machine learning techniques by penal-izing the models during training. Such approaches act in either the input, internal, or output layers. Regarding the latter, label smooth-ing is widely used to introduce noise in the label vector, making learning more challenging. This work proposes a new label regular- WebApr 9, 2024 · Where: n is the number of data points; y_i is the true label of the i’th training example. It can be +1 or -1. x_i is the feature vector of the i’th training example. w is the weight vector ... electoral autocracy meaning
python - Label Smoothing in PyTorch - Stack Overflow
WebOur theoretical results are based on interpret- ing label smoothing as a regularization technique and quantifying the tradeo s between estimation and regu- larization. These results also allow us to predict where the optimal label smoothing point lies for the best per- … Webfrom the perspective of Label Smoothing Regularization (LSR) [16] that regularizes model training by replacing the one-hot labels with smoothed ones. We then analyze … WebMay 18, 2024 · Regularization of (deep) learning models can be realized at the model, loss, or data level. As a technique somewhere in-between loss and data, label smoothing turns deterministic class labels into probability distributions, for example by uniformly distributing a certain part of the probability mass over all classes. A predictive model is then trained … foodroots ag