Sungbin Lim

Orcid: 0000-0003-2684-2022

According to our database1, Sungbin Lim authored at least 23 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
Minimax Optimal Bandits for Heavy Tail Rewards.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

Slice and Conquer: A Planar-to-3D Framework for Efficient Interactive Segmentation of Volumetric Images.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023
Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms?
CoRR, 2023

Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs.
CoRR, 2023

Score-based Generative Models with Lévy Processes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Score-based Generative Modeling through Stochastic Evolution Equations in Hilbert Spaces.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bag of Tricks for In-Distribution Calibration of Pretrained Transformers.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

2021
A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drone.
CoRR, 2021

Neural Bootstrapper.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Evaluation of conditional treatment effects of adjuvant treatments on patients with synovial sarcoma using Bayesian subgroup analysis.
BMC Medical Informatics Decis. Mak., December, 2020

Neural Bootstrapper.
CoRR, 2020

AutoCLINT: The Winning Method in AutoCV Challenge 2019.
CoRR, 2020

torchgpipe: On-the-fly Pipeline Parallelism for Training Giant Models.
CoRR, 2020

Generalized Tsallis Entropy Reinforcement Learning and Its Application to Soft Mobile Robots.
Proceedings of the Robotics: Science and Systems XVI, 2020

Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning.
CoRR, 2019

Fast AutoAugment.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Scalable Neural Architecture Search for 3D Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

2018
ChoiceNet: Robust Learning by Revealing Output Correlations.
CoRR, 2018

Uncertainty-Aware Learning from Demonstration Using Mixture Density Networks with Sampling-Free Variance Modeling.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017
Neural Stain-Style Transfer Learning using GAN for Histopathological Images.
CoRR, 2017


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