101 citations · 301 across the 44 of their papers we have counts for
5 papers · 1 filter
Efficient Neural Network Compression
Hyeji Kim, Muhammad Umar Karim Khan, Chong-Min Kyung
Network compression reduces the computational complexity and memory consumption of deep neural networks by reducing the number of parameters. In SVD-based network compression, the…
LEARN Codes: Inventing Low-latency Codes via Recurrent Neural Networks
Yihan Jiang, Hyeji Kim, Himanshu Asnani +3
Designing channel codes under low-latency constraints is one of the most demanding requirements in 5G standards. However, a sharp characterization of the performance of traditional…
Deepcode: Feedback Codes via Deep Learning
Hyeji Kim, Yihan Jiang, Sreeram Kannan +2
The design of codes for communicating reliably over a statistically well defined channel is an important endeavor involving deep mathematical research and wide-ranging practical ap…
Automatic Rank Selection for High-Speed Convolutional Neural Network
Hyeji Kim, Chong-Min Kyung
Low-rank decomposition plays a central role in accelerating convolutional neural network (CNN), and the rank of decomposed kernel-tensor is a key parameter that determines the comp…
Communication Algorithms via Deep Learning
Hyeji Kim, Yihan Jiang, Ranvir Rana +3
Coding theory is a central discipline underpinning wireline and wireless modems that are the workhorses of the information age. Progress in coding theory is largely driven by indiv…