85 citations · 155 across the 9 of their papers we have counts for
4 papers · 1 filter
SimEx: Express Prediction of Inter-dataset Similarity by a Fleet of Autoencoders
Inseok Hwang, Jinho Lee, Frank Liu +1
Knowing the similarity between sets of data has a number of positive implications in training an effective model, such as assisting an informed selection out of known datasets favo…
MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design
Mayoore S. Jaiswal, Bumsoo Kang, Jinho Lee +1
Target encoding is an effective technique to deliver better performance for conventional machine learning methods, and recently, for deep neural networks as well. However, the exis…
A Unified Approximation Framework for Compressing and Accelerating Deep Neural Networks
Yuzhe Ma, Ran Chen, Wei Li +4
Deep neural networks (DNNs) have achieved significant success in a variety of real world applications, i.e., image classification. However, tons of parameters in the networks restr…
MEC: Memory-efficient Convolution for Deep Neural Network
Minsik Cho, Daniel Brand
Convolution is a critical component in modern deep neural networks, thus several algorithms for convolution have been developed. Direct convolution is simple but suffers from poor…