Sungbin Lim | DeepAI

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Featured Co-authors

Sungjoon Choi
23 publications
Songhwai Oh
23 publications
Sungwoong Kim
19 publications
Kyungjae Lee
18 publications
Jaeyoung Kim
18 publications
Taesup Kim
15 publications
Sungchul Choi
10 publications
Hyokun Yun
10 publications
Chiheon Kim
10 publications
Ildoo Kim
9 publications
Minsuk Shin
7 publications

∙ 08/01/2023

Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs

Finding a high-quality feasible solution to a combinatorial optimization...

0 Taehyun Yoon, et al. ∙

∙ 02/13/2023

Bag of Tricks for In-Distribution Calibration of Pretrained Transformers

While pre-trained language models (PLMs) have become a de-facto standard...

0 Jaeyoung Kim, et al. ∙

∙ 12/22/2021

A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drone

Reinforcement learning has recently shown promise in learning quality so...

0 Aigerim Bogyrbayeva, et al. ∙

∙ 10/24/2020

Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards

In this paper, we consider stochastic multi-armed bandits (MABs) with he...

0 Kyungjae Lee, et al. ∙

∙ 10/02/2020

Neural Bootstrapper

Bootstrapping has been a primary tool for uncertainty quantification, an...

0 Minsuk Shin, et al. ∙

∙ 05/09/2020

AutoCLINT: The Winning Method in AutoCV Challenge 2019

NeurIPS 2019 AutoDL challenge is a series of six automated machine learn...

0 Woonhyuk Baek, et al. ∙

∙ 04/21/2020

torchgpipe: On-the-fly Pipeline Parallelism for Training Giant Models

We design and implement a ready-to-use library in PyTorch for performing...

0 Chiheon Kim, et al. ∙

∙ 06/13/2019

Scalable Neural Architecture Search for 3D Medical Image Segmentation

In this paper, a neural architecture search (NAS) framework is proposed ...

0 Sungwoong Kim, et al. ∙

∙ 05/01/2019

Fast AutoAugment

Data augmentation is an indispensable technique to improve generalizatio...

0 Sungbin Lim, et al. ∙

∙ 01/31/2019

Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning

In this paper, we present a new class of Markov decision processes (MDPs...

0 Kyungjae Lee, et al. ∙

∙ 05/16/2018

ChoiceNet: Robust Learning by Revealing Output Correlations

In this paper, we focus on the supervised learning problem with corrupte...

0 Sungjoon Choi, et al. ∙

∙ 10/23/2017

Neural Stain-Style Transfer Learning using GAN for Histopathological Images

Performance of data-driven network for tumor classification varies with ...

0 Hyungjoo Cho, et al. ∙

∙ 09/03/2017

Uncertainty-Aware Learning from Demonstration using Mixture Density Networks with Sampling-Free Variance Modeling

In this paper, we propose an uncertainty-aware learning from demonstrati...

0 Sungjoon Choi, et al. ∙

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