python代码实现如上,这玩意可以看作relu版的softmax,把softmax变分段了。由此可以引申出sparsemax的activation和sparsemax loss function。 编辑于 2021-10-06 09:40 softmax 深度学习(Deep Learning) 梯度消失问题 赞同2914 条评论 分享喜欢收藏申请转载 ...
函数 基本使用 function 函数名(形参1,形参2, ...){ //函数体(代码块)} 1,没有返回值的函数,调用语句为独立语句。函数名(实参1,实参2,...); 2,具有返回值的函数,调用语句会掺杂在别的语句中,把该函数当做一个数据使用: 函数定义形式 函数调用形式 函数调用流程分析 开始调用:实际参数传递...函数 ...
Sparsemax is a type of activation/output function similar to the traditional softmax, but able to output sparse probabilities. $$ \text{sparsemax}\left(z\right) = \arg_{p∈\Delta^{K−1}}\min||\mathbf{p} - \mathbf{z}||^{2} $$ ...
ive summarization models mostly rely on Sequence-to-Sequence architectures, in which the softmax function is widely used to transform the model output to simplex. However, softmax's output probability distribution often has the long-tail effect especially when the vocabulary size is large. Many ...
dom(⋅) a domain of a function 1(⋅) Indicator function ∥⋅∥ ℓ2 norm Tr(⋅) the trace of a matrix. log(⋅) the natural logarithm.Table 2. Statistics of All Data SetsData set # Documents Vocabulary Avg doc len Data set # Documents Size by words Twitter (S) 54,000,648...
We propose sparsemax, a new activation function similar to the traditional softmax, but able to output sparse probabilities. After deriving its properties, we show how its Jacobian can be efficiently computed, enabling its use in a network trained with backpropagation. Then, we propose a new smo...
In this paper, we formulate a novel loss function, called Angular Sparsemax for face recognition. The proposed loss function promotes sparseness of the hypotheses prediction function similar to Sparsemax [1] with Fenchel-Young regularisation. By introducing an additive angular margin on the score ...