6 citations · 14 across the 6 of their papers we have counts for
6 papers
GeNAS: Neural Architecture Search with Better Generalization
Joonhyun Jeong, Joonsang Yu, Geondo Park +2
Neural Architecture Search (NAS) aims to automatically excavate the optimal network architecture with superior test performance. Recent neural architecture search (NAS) approaches…
BiTAT: Neural Network Binarization with Task-dependent Aggregated Transformation
Geon Park, Jaehong Yoon, Haiyang Zhang +3
Neural network quantization aims to transform high-precision weights and activations of a given neural network into low-precision weights/activations for reduced memory usage and c…
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization
Jaehong Yoon, Geon Park, Wonyong Jeong +1
In practical federated learning scenarios, the participating devices may have different bitwidths for computation and memory storage by design. However, despite the progress made i…
Distilling Linguistic Context for Language Model Compression
Geondo Park, Gyeongman Kim, Eunho Yang
A computationally expensive and memory intensive neural network lies behind the recent success of language representation learning. Knowledge distillation, a major technique for de…
Attribution Preservation in Network Compression for Reliable Network Interpretation
Geondo Park, June Yong Yang, Sung Ju Hwang +1
Neural networks embedded in safety-sensitive applications such as self-driving cars and wearable health monitors rely on two important techniques: input attribution for hindsight a…
MHSAN: Multi-Head Self-Attention Network for Visual Semantic Embedding
Geondo Park, Chihye Han, Wonjun Yoon +1
Visual-semantic embedding enables various tasks such as image-text retrieval, image captioning, and visual question answering. The key to successful visual-semantic embedding is to…