7.5k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- NAVER Cloud (South Korea)KR46 papers
- Seoul National UniversityKR27 papers
- Korea Advanced Institute of Science and TechnologyKR24 papers
- Yonsei UniversityKR17 papers
- Sungkyunkwan UniversityKR12 papers
- Korea UniversityKR9 papers
- Line Corporation (Japan)JP5 papers
- Virginia TechUS5 papers
- Inha UniversityKR4 papers
- Kootenay Association for Science & TechnologyCA4 papers
- University of TorontoCA4 papers
- Hong Kong University of Science and TechnologyHK3 papers
21 papers · 1 filter
ST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Road Speed
Cheonbok Park, Chunggi Lee, Hyojin Bahng +5
Predicting road traffic speed is a challenging task due to different types of roads, abrupt speed change and spatial dependencies between roads; it requires the modeling of dynamic…
Efficient Dialogue State Tracking by Selectively Overwriting Memory
Sungdong Kim, Sohee Yang, Gyuwan Kim +1
Recent works in dialogue state tracking (DST) focus on an open vocabulary-based setting to resolve scalability and generalization issues of the predefined ontology-based approaches…
The sound of my voice: speaker representation loss for target voice separation
Seongkyu Mun, Soyeon Choe, Jaesung Huh +1
Content and style representations have been widely studied in the field of style transfer. In this paper, we propose a new loss function using speaker content representation for au…
Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram
Ryuichi Yamamoto, Eunwoo Song, Jae-Min Kim
We propose Parallel WaveGAN, a distillation-free, fast, and small-footprint waveform generation method using a generative adversarial network. In the proposed method, a non-autoreg…
Self-supervised pre-training with acoustic configurations for replay spoofing detection
Hye-jin Shim, Hee-Soo Heo, Jee-weon Jung +1
Constructing a dataset for replay spoofing detection requires a physical process of playing an utterance and re-recording it, presenting a challenge to the collection of large-scal…
Learning De-biased Representations with Biased Representations
Hyojin Bahng, Sanghyuk Chun, Sangdoo Yun +2
Many machine learning algorithms are trained and evaluated by splitting data from a single source into training and test sets. While such focus on in-distribution learning scenario…
Solving Continual Combinatorial Selection via Deep Reinforcement Learning
Hyungseok Song, Hyeryung Jang, Hai H. Tran +5
We consider the Markov Decision Process (MDP) of selecting a subset of items at each step, termed the Select-MDP (S-MDP). The large state and action spaces of S-MDPs make them intr…
Subword Language Model for Query Auto-Completion
Gyuwan Kim
Current neural query auto-completion (QAC) systems rely on character-level language models, but they slow down when queries are long. We present how to utilize subword language mod…
A Quantile-based Approach for Hyperparameter Transfer Learning
David Salinas, Huibin Shen, Valerio Perrone
Bayesian optimization (BO) is a popular methodology to tune the hyperparameters of expensive black-box functions. Traditionally, BO focuses on a single task at a time and is not de…
PopEval: A Character-Level Approach to End-To-End Evaluation Compatible with Word-Level Benchmark Dataset
Hong-Seok Lee, Youngmin Yoon, Pil-Hoon Jang +1
The most prevalent scope of interest for OCR applications used to be scanned documents, but it has now shifted towards the natural scene. Despite the change of times, the existing…
Key Protected Classification for Collaborative Learning
Mert Bülent Sarıyıldız, Ramazan Gökberk Cinbiş, Erman Ayday
Large-scale datasets play a fundamental role in training deep learning models. However, dataset collection is difficult in domains that involve sensitive information. Collaborative…
ExtremeC3Net: Extreme Lightweight Portrait Segmentation Networks using Advanced C3-modules
Hyojin Park, Lars Lowe Sjösund, YoungJoon Yoo +2
Designing a lightweight and robust portrait segmentation algorithm is an important task for a wide range of face applications. However, the problem has been considered as a subset…
Tripartite Heterogeneous Graph Propagation for Large-scale Social Recommendation
Kyung-Min Kim, Donghyun Kwak, Hanock Kwak +7
Graph Neural Networks (GNNs) have been emerging as a promising method for relational representation including recommender systems. However, various challenging issues of social gra…
Learning with Average Precision: Training Image Retrieval with a Listwise Loss
Jerome Revaud, Jon Almazan, Rafael Sampaio de Rezende +1
Image retrieval can be formulated as a ranking problem where the goal is to order database images by decreasing similarity to the query. Recent deep models for image retrieval have…
Comparing Machine Learning Approaches for Table Recognition in Historical Register Books
Stéphane Clinchant, Hervé Déjean, Jean-Luc Meunier +2
We present in this paper experiments on Table Recognition in hand-written registry books. We first explain how the problem of row and column detection is modeled, and then compare…
Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning
Wonjae Kim, Yoonho Lee
Without relevant human priors, neural networks may learn uninterpretable features. We propose Dynamics of Attention for Focus Transition (DAFT) as a human prior for machine reasoni…
GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images
Sungmin Cha, Taeeon Park, Byeongjoon Kim +2
We tackle a challenging blind image denoising problem, in which only single distinct noisy images are available for training a denoiser, and no information about noise is known, ex…
Phase-aware Speech Enhancement with Deep Complex U-Net
Hyeong-Seok Choi, Jang-Hyun Kim, Jaesung Huh +3
Most deep learning-based models for speech enhancement have mainly focused on estimating the magnitude of spectrogram while reusing the phase from noisy speech for reconstruction.…
Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation
Sang-Woo Lee, Tong Gao, Sohee Yang +2
Answerer in Questioner's Mind (AQM) is an information-theoretic framework that has been recently proposed for task-oriented dialog systems. AQM benefits from asking a question that…
A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization
Wonseok Hwang, Jinyeong Yim, Seunghyun Park +1
We present SQLova, the first Natural-language-to-SQL (NL2SQL) model to achieve human performance in WikiSQL dataset. We revisit and discuss diverse popular methods in NL2SQL litera…
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim +4
Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting va…