8 citations · 37 across the 10 of their papers we have counts for
12 papers
VQ-AR: Vector Quantized Autoregressive Probabilistic Time Series Forecasting
Kashif Rasul, Young-Jin Park, Max Nihlén Ramström +1
Time series models aim for accurate predictions of the future given the past, where the forecasts are used for important downstream tasks like business decision making. In practice…
Hazard Gradient Penalty for Survival Analysis
Seungjae Jung, Kyung-Min Kim
Survival analysis appears in various fields such as medicine, economics, engineering, and business. Recent studies showed that the Ordinary Differential Equation (ODE) modeling fra…
Metropolis-Hastings Data Augmentation for Graph Neural Networks
Hyeonjin Park, Seunghun Lee, Sihyeon Kim +5
Graph Neural Networks (GNNs) often suffer from weak-generalization due to sparsely labeled data despite their promising results on various graph-based tasks. Data augmentation is a…
Intent-based Product Collections for E-commerce using Pretrained Language Models
Hiun Kim, Jisu Jeong, Kyung-Min Kim +7
Building a shopping product collection has been primarily a human job. With the manual efforts of craftsmanship, experts collect related but diverse products with common shopping i…
Global-Local Item Embedding for Temporal Set Prediction
Seungjae Jung, Young-Jin Park, Jisu Jeong +4
Temporal set prediction is becoming increasingly important as many companies employ recommender systems in their online businesses, e.g., personalized purchase prediction of shoppi…
One4all User Representation for Recommender Systems in E-commerce
Kyuyong Shin, Hanock Kwak, Kyung-Min Kim +4
General-purpose representation learning through large-scale pre-training has shown promising results in the various machine learning fields. For an e-commerce domain, the objective…