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  /frameworks/ml/bordeaux/learning/stochastic_linear_ranker/native/
sparse_weight_vector.cpp 303 void SparseWeightVector<Key, Hash>::ReprojectL1(const double l1_norm) {
309 CHECK_GT(l1_norm, 0);
320 if (curr_l1_norm < l1_norm) {
333 theta = (cum_sum - l1_norm)/curr_index;
sparse_weight_vector.h 154 void ReprojectL1(const double l1_norm);
  /external/webrtc/src/modules/audio_processing/aec/
echo_cancellation.c 809 float l1_norm = 0; local
859 l1_norm += (float) (fabs(i - my_median) * self->aec->delay_histogram[i]);
861 *std = (int) (l1_norm / (float) num_delay_values + 0.5f) * kMsPerBlock;

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