3 papers
cs.LG2019
Compiler-Level Matrix Multiplication Optimization for Deep Learning
Huaqing Zhang, Xiaolin Cheng, Hui Zang +1
An important linear algebra routine, GEneral Matrix Multiplication (GEMM), is a fundamental operator in deep learning. Compilers need to translate these routines into low-level cod…
cs.LG2018
Gradient-Coherent Strong Regularization for Deep Neural Networks
Dae Hoon Park, Chiu Man Ho, Yi Chang +1
Regularization plays an important role in generalization of deep neural networks, which are often prone to overfitting with their numerous parameters. L1 and L2 regularizers are co…
cs.IR2018
Adversarial Sampling and Training for Semi-Supervised Information Retrieval
Dae Hoon Park, Yi Chang
Ad-hoc retrieval models with implicit feedback often have problems, e.g., the imbalanced classes in the data set. Too few clicked documents may hurt generalization ability of the m…