170 citations · 191 across the 5 of their papers we have counts for
5 papers
Accelerating Multi-Model Inference by Merging DNNs of Different Weights
Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu +2
Standardized DNN models that have been proved to perform well on machine learning tasks are widely used and often adopted as-is to solve downstream tasks, forming the transfer lear…
Hippo: Taming Hyper-parameter Optimization of Deep Learning with Stage Trees
Ahnjae Shin, Do Yoon Kim, Joo Seong Jeong +1
Hyper-parameter optimization is crucial for pushing the accuracy of a deep learning model to its limits. A hyper-parameter optimization job, referred to as a study, involves numero…
JANUS: Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs
Eunji Jeong, Sungwoo Cho, Gyeong-In Yu +3
The rapid evolution of deep neural networks is demanding deep learning (DL) frameworks not only to satisfy the requirement of quickly executing large computations, but also to supp…
Improving the Expressiveness of Deep Learning Frameworks with Recursion
Eunji Jeong, Joo Seong Jeong, Soojeong Kim +2
Recursive neural networks have widely been used by researchers to handle applications with recursively or hierarchically structured data. However, embedded control flow deep learni…
Coexistence of Intrinsic Superconductivity and Topological Insulator State in Monoclinic Phase WS2
Yuqiang Fang, Jie Pan, Dongqin Zhang +14
Recently, intriguing phenomena of superconductivity, type-II Weyl semimetal or quantum spin Hall states were discovered in metastable 1T'-type VIB-group transition metal dichalcoge…