activity
20182021
most citedMEANTIME: Mixture of Attention Mechanisms with Multi-temporal Embeddings for Sequential Recommendation

61 citations · 71 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CV2021

Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation

Hyunyoung Jung, Eunhyeok Park, Sungjoo Yoo

Self-supervised monocular depth estimation has been widely studied, owing to its practical importance and recent promising improvements. However, most works suffer from limited sup…

cs.CV2021

Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing

Hyunsu Kim, Yunjey Choi, Junho Kim +2

Generative adversarial networks (GANs) synthesize realistic images from random latent vectors. Although manipulating the latent vectors controls the synthesized outputs, editing re…

cs.LG202061 cited

MEANTIME: Mixture of Attention Mechanisms with Multi-temporal Embeddings for Sequential Recommendation

Sung Min Cho, Eunhyeok Park, Sungjoo Yoo

Recently, self-attention based models have achieved state-of-the-art performance in sequential recommendation task. Following the custom from language processing, most of these mod…

cs.CV2020

PROFIT: A Novel Training Method for sub-4-bit MobileNet Models

Eunhyeok Park, Sungjoo Yoo

4-bit and lower precision mobile models are required due to the ever-increasing demand for better energy efficiency in mobile devices. In this work, we report that the activation i…

cs.CV201810 cited

Precision Highway for Ultra Low-Precision Quantization

Eunhyeok Park, Dongyoung Kim, Sungjoo Yoo +1

Neural network quantization has an inherent problem called accumulated quantization error, which is the key obstacle towards ultra-low precision, e.g., 2- or 3-bit precision. To re…

cs.LG2018

Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications

Jongsoo Park, Maxim Naumov, Protonu Basu +25

The application of deep learning techniques resulted in remarkable improvement of machine learning models. In this paper provides detailed characterizations of deep learning models…