A convolutional layer combined with a number of wide convolutional filters is applied to E S .
the k-th convolutional filter operator filter k involves a weight vector w k ∈ R m×t , which works on every t k -sized window of E S , and is accompanied by a bias term b ∈ R. The filter operator is followed by the non-linear function F , a rectified linear unit, ReLU, followed by a maxpooling operation, to generate a hidden activation h k = MaxPooling(F (filter k (E S ; w k , b)).