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Jinsung Yoon
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2020 – today
- 2024
- [j21]Sung-Jin Lee
, Bit Kim, Dongwook Yang
A compact RTK-GNSS device for high-precision localization of outdoor mobile robots. J. Field Robotics 41(5): 1349-1365 (2024) - [j20]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister:
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. Trans. Mach. Learn. Res. 2024 (2024) - [j19]Zachary Izzo, Jinsung Yoon, Sercan Ö. Arik, James Zou:
Provable Membership Inference Privacy. Trans. Mach. Learn. Res. 2024 (2024) - [c35]Jinsung Yoon, Yanfei Chen, Sercan Ö. Arik, Tomas Pfister:
Search-Adaptor: Embedding Customization for Information Retrieval. ACL (1) 2024: 12230-12247 - [c34]Yanfei Chen, Jinsung Yoon, Devendra Singh Sachan, Qingze Wang, Vincent Cohen-Addad, MohammadHossein Bateni, Chen-Yu Lee, Tomas Pfister:
Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrieval. EMNLP (Findings) 2024: 4705-4726 - [c33]Jinsung Yoon, Rajarishi Sinha, Sercan Ömer Arik, Tomas Pfister:
Matryoshka-Adaptor: Unsupervised and Supervised Tuning for Smaller Embedding Dimensions. EMNLP 2024: 10318-10336 - [c32]Sungwon Han, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister:
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning. ICML 2024 - [i45]Sungwon Han, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister:
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning. CoRR abs/2404.09491 (2024) - [i44]Hyunsung Kim, Gun-Hee Joe, Jinsung Yoon, Sang-Ki Ko:
Contextual Sprint Classification in Soccer Based on Deep Learning. CoRR abs/2406.15659 (2024) - [i43]Hongjin Su, Howard Yen, Mengzhou Xia, Weijia Shi, Niklas Muennighoff, Han-yu Wang, Haisu Liu, Quan Shi, Zachary S. Siegel, Michael Tang, Ruoxi Sun, Jinsung Yoon, Sercan Ö. Arik, Danqi Chen, Tao Yu:
BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval. CoRR abs/2407.12883 (2024) - [i42]Jinsung Yoon, Rajarishi Sinha, Sercan Ö. Arik, Tomas Pfister:
Matryoshka-Adaptor: Unsupervised and Supervised Tuning for Smaller Embedding Dimensions. CoRR abs/2407.20243 (2024) - [i41]Yanfei Chen, Jinsung Yoon, Devendra Singh Sachan, Qingze Wang, Vincent Cohen-Addad, MohammadHossein Bateni, Chen-Yu Lee, Tomas Pfister:
Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrieval. CoRR abs/2408.01875 (2024) - [i40]Hanjun Choi, Hyunsung Kim, Minho Lee, Changjo Kim, Jinsung Yoon, Sang-Ki Ko:
DBHP: Trajectory Imputation in Multi-Agent Sports Using Derivative-Based Hybrid Prediction. CoRR abs/2408.10878 (2024) - [i39]Bowen Jin, Jinsung Yoon, Jiawei Han, Sercan Ö. Arik:
Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG. CoRR abs/2410.05983 (2024) - 2023
- [j18]Jinsung Yoon
EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records. npj Digit. Medicine 6 (2023) - [j17]Mingu Kim
The Design of GNSS/IMU Loosely-Coupled Integration Filter for Wearable EPTS of Football Players. Sensors 23(4): 1749 (2023) - [j16]Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister:
Invariant Structure Learning for Better Generalization and Causal Explainability. Trans. Mach. Learn. Res. 2023 (2023) - [j15]Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister:
Interpretable Mixture of Experts. Trans. Mach. Learn. Res. 2023 (2023) - [j14]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister:
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. Trans. Mach. Learn. Res. 2023 (2023) - [c31]Min Jae Lee, Kyunghoon Hur, Jiyoun Kim, Jinsung Yoon, Edward Choi:
Rediscovery of CNN's Versatility for Text-based Encoding of Raw Electronic Health Records. CHIL 2023: 294-313 - [c30]Jinsung Yoon, Donghyun Lee, Neungyun Kim, Su-Jung Lee, Gil-Ho Kwak, Tae-Hwan Kim:
A Real-Time Keyword Spotting System Based on an End-To-End Binary Convolutional Neural Network in FPGA. COOL CHIPS 2023: 1-3 - [c29]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha:
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. EMNLP (Findings) 2023: 5190-5213 - [c28]Chun-Hao Chang
Data-Efficient and Interpretable Tabular Anomaly Detection. KDD 2023: 190-201 - [c27]Hyunsung Kim
Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM. KDD 2023: 4296-4307 - [c26]Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister:
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. WACV 2023: 5468-5479 - [i38]Eunbyeol Cho, Min Jae Lee, Kyunghoon Hur, Jiyoun Kim, Jinsung Yoon, Edward Choi:
Rediscovery of CNN's Versatility for Text-based Encoding of Raw Electronic Health Records. CoRR abs/2303.08290 (2023) - [i37]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister:
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. CoRR abs/2304.03870 (2023) - [i36]Hyunsung Kim, Han-Jun Choi, Changjo Kim, Jinsung Yoon, Sang-Ki Ko:
Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM. CoRR abs/2306.08206 (2023) - [i35]Nicasia Beebe-Wang, Sayna Ebrahimi, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister:
PAITS: Pretraining and Augmentation for Irregularly-Sampled Time Series. CoRR abs/2308.13703 (2023) - [i34]Jinsung Yoon, Sercan Ö. Arik, Yanfei Chen, Tomas Pfister:
Search-Adaptor: Text Embedding Customization for Information Retrieval. CoRR abs/2310.08750 (2023) - [i33]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha:
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. CoRR abs/2310.11689 (2023) - [i32]Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole
Clairvoyance: A Pipeline Toolkit for Medical Time Series. CoRR abs/2310.18688 (2023) - 2022
- [j13]Jeongbin Kim, Hyunsung Kim
A Deep Learning Approach for Fatigue Prediction in Sports Using GPS Data and Rate of Perceived Exertion. IEEE Access 10: 103056-103064 (2022) - [j12]Thomas C. Tsai
Algorithmic fairness in pandemic forecasting: lessons from COVID-19. npj Digit. Medicine 5 (2022) - [j11]Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister:
LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling. Trans. Mach. Learn. Res. 2022 (2022) - [j10]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister:
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection. Trans. Mach. Learn. Res. 2022 (2022) - [c25]Hyunsung Kim
SoccerCPD: Formation and Role Change-Point Detection in Soccer Matches Using Spatiotemporal Tracking Data. KDD 2022: 3146-3156 - [c24]Hyunsung Kim
Cost-Efficient and Bias-Robust Sports Player Tracking by Integrating GPS and Video. MLSA@PKDD/ECML 2022: 74-86 - [i31]Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister:
Towards Group Robustness in the presence of Partial Group Labels. CoRR abs/2201.03668 (2022) - [i30]Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister:
Data-Efficient and Interpretable Tabular Anomaly Detection. CoRR abs/2203.02034 (2022) - [i29]Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister:
Interpretable Mixture of Experts for Structured Data. CoRR abs/2206.02107 (2022) - [i28]Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister:
Invariant Structure Learning for Better Generalization and Causal Explainability. CoRR abs/2206.06469 (2022) - [i27]Zachary Izzo, Jinsung Yoon, Sercan Ö. Arik, James Zou:
Provable Membership Inference Privacy. CoRR abs/2211.06582 (2022) - [i26]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister:
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. CoRR abs/2212.00173 (2022) - 2021
- [j9]Sercan Ö. Arik
A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. npj Digit. Medicine 4 (2021) - [c23]Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister:
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CVPR 2021: 9664-9674 - [c22]Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar:
Clairvoyance: A Pipeline Toolkit for Medical Time Series. ICLR 2021 - [c21]Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister:
Learning and Evaluating Representations for Deep One-Class Classification. ICLR 2021 - [c20]Sungyong Seo, Sercan Ö. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister:
Controlling Neural Networks with Rule Representations. NeurIPS 2021: 11196-11207 - [c19]Hyunsung Kim
6MapNet: Representing Soccer Players from Tracking Data by a Triplet Network. MLSA@PKDD/ECML 2021: 3-14 - [i25]Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister:
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CoRR abs/2104.04015 (2021) - [i24]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister:
Self-Trained One-class Classification for Unsupervised Anomaly Detection. CoRR abs/2106.06115 (2021) - [i23]Sungyong Seo, Sercan Ö. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister:
Controlling Neural Networks with Rule Representations. CoRR abs/2106.07804 (2021) - [i22]Hyunsung Kim, Jihun Kim, Dongwook Chung, Jonghyun Lee, Jinsung Yoon, Sang-Ki Ko:
6MapNet: Representing soccer players from tracking data by a triplet network. CoRR abs/2109.04720 (2021) - [i21]Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister:
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. CoRR abs/2112.11573 (2021) - 2020
- [b1]Jinsung Yoon:
End-to-End Machine Learning Frameworks for Medicine: Data Imputation, Model Interpretation and Synthetic Data Generation. University of California, Los Angeles, USA, 2020 - [j8]Changhee Lee
Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data. IEEE Trans. Biomed. Eng. 67(1): 122-133 (2020) - [j7]Daniel Jarrett
Dynamic Prediction in Clinical Survival Analysis Using Temporal Convolutional Networks. IEEE J. Biomed. Health Informatics 24(2): 424-436 (2020) - [j6]Jinsung Yoon
Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN). IEEE J. Biomed. Health Informatics 24(8): 2378-2388 (2020) - [c18]Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister:
Data Valuation using Reinforcement Learning. ICML 2020: 10842-10851 - [c17]Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister:
Interpretable Sequence Learning for Covid-19 Forecasting. NeurIPS 2020 - [c16]James Jordon, Daniel Jarrett, Evgeny Saveliev, Jinsung Yoon, Paul W. G. Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar:
Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification. NeurIPS (Competition and Demos) 2020: 206-215 - [c15]Jinsung Yoon, Yao Zhang, James Jordon, Mihaela van der Schaar:
VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain. NeurIPS 2020 - [i20]James Jordon, Daniel Jarrett, Jinsung Yoon, Tavian Barnes, Paul W. G. Elbers, Patrick Thoral, Ari Ercole
Hide-and-Seek Privacy Challenge. CoRR abs/2007.12087 (2020) - [i19]Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister:
Interpretable Sequence Learning for COVID-19 Forecasting. CoRR abs/2008.00646 (2020) - [i18]Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister:
Learning and Evaluating Representations for Deep One-class Classification. CoRR abs/2011.02578 (2020)
2010 – 2019
- 2019
- [j5]Jinsung Yoon
Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks. IEEE Trans. Biomed. Eng. 66(5): 1477-1490 (2019) - [c14]James Jordon, Jinsung Yoon, Mihaela van der Schaar:
KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks. ICLR 2019 - [c13]James Jordon, Jinsung Yoon, Mihaela van der Schaar:
PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees. ICLR (Poster) 2019 - [c12]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
INVASE: Instance-wise Variable Selection using Neural Networks. ICLR (Poster) 2019 - [c11]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
ASAC: Active Sensing using Actor-Critic models. MLHC 2019: 451-473 - [c10]James Jordon, Jinsung Yoon, Mihaela van der Schaar:
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate. NeurIPS 2019: 4325-4334 - [c9]Jinsung Yoon, Daniel Jarrett, Mihaela van der Schaar:
Time-series Generative Adversarial Networks. NeurIPS 2019: 5509-5519 - [i17]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
ASAC: Active Sensing using Actor-Critic models. CoRR abs/1906.06796 (2019) - [i16]Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister:
Data Valuation using Reinforcement Learning. CoRR abs/1909.11671 (2019) - [i15]Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister:
RL-LIM: Reinforcement Learning-based Locally Interpretable Modeling. CoRR abs/1909.12367 (2019) - 2018
- [j4]Ahmed M. Alaa
Personalized Risk Scoring for Critical Care Prognosis Using Mixtures of Gaussian Processes. IEEE Trans. Biomed. Eng. 65(1): 207-218 (2018) - [j3]Jinsung Yoon
ToPs: Ensemble Learning With Trees of Predictors. IEEE Trans. Signal Process. 66(8): 2141-2152 (2018) - [c8]Changhee Lee, William R. Zame, Jinsung Yoon, Mihaela van der Schaar:
DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks. AAAI 2018: 2314-2321 - [c7]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets. ICLR (Poster) 2018 - [c6]Jinsung Yoon, William R. Zame, Mihaela van der Schaar:
Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks. ICLR (Poster) 2018 - [c5]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
GAIN: Missing Data Imputation using Generative Adversarial Nets. ICML 2018: 5675-5684 - [c4]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks. ICML 2018: 5685-5693 - [p1]Honglei Li, Yanzhou Liu, Kishan Sudusinghe, Jinsung Yoon, Erik Blasch, Mihaela van der Schaar, Shuvra S. Bhattacharyya:
Design of a Dynamic Data-Driven System for Multispectral Video Processing. Handbook of Dynamic Data Driven Applications Systems 2018: 529-545 - [i14]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks. CoRR abs/1802.06403 (2018) - [i13]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
GAIN: Missing Data Imputation using Generative Adversarial Nets. CoRR abs/1806.02920 (2018) - [i12]James Jordon, Jinsung Yoon, Mihaela van der Schaar:
Measuring the quality of Synthetic data for use in competitions. CoRR abs/1806.11345 (2018) - [i11]Carl Rietschel, Jinsung Yoon, Mihaela van der Schaar:
Feature Selection for Survival Analysis with Competing Risks using Deep Learning. CoRR abs/1811.09317 (2018) - [i10]Daniel Jarrett, Jinsung Yoon, Mihaela van der Schaar:
MATCH-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks. CoRR abs/1811.10746 (2018) - 2017
- [j2]Jinsung Yoon
Discovery and Clinical Decision Support for Personalized Healthcare. IEEE J. Biomed. Health Informatics 21(4): 1133-1145 (2017) - [j1]Cem Tekin, Jinsung Yoon, Mihaela van der Schaar
Adaptive Ensemble Learning With Confidence Bounds. IEEE Trans. Signal Process. 65(4): 888-903 (2017) - [c3]Jinsung Yoon, Ahmed M. Alaa, Martin Cadeiras, Mihaela van der Schaar:
Personalized Donor-Recipient Matching for Organ Transplantation. AAAI 2017: 1647-1654 - [i9]Jinsung Yoon, William R. Zame, Amitava Banerjee, Martin Cadeiras, Ahmed M. Alaa, Mihaela van der Schaar:
Personalized Survival Predictions for Cardiac Transplantation via Trees of Predictors. CoRR abs/1704.03458 (2017) - [i8]Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar:
Individualized Risk Prognosis for Critical Care Patients: A Multi-task Gaussian Process Model. CoRR abs/1705.07674 (2017) - [i7]Jinsung Yoon, William R. Zame, Mihaela van der Schaar:
ToPs: Ensemble Learning with Trees of Predictors. CoRR abs/1706.01396 (2017) - [i6]Jinsung Yoon, William R. Zame, Mihaela van der Schaar:
Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks. CoRR abs/1711.08742 (2017) - 2016
- [c2]Cem Tekin, Jinsung Yoon, Mihaela van der Schaar:
Adaptive Ensemble Learning with Confidence Bounds for Personalized Diagnosis. AAAI Workshop: Expanding the Boundaries of Health Informatics Using AI 2016 - [c1]Jinsung Yoon, Ahmed M. Alaa, Scott Hu, Mihaela van der Schaar:
ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission. ICML 2016: 1680-1689 - [i5]Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar:
Personalized Risk Scoring for Critical Care Patients using Mixtures of Gaussian Process Experts. CoRR abs/1605.00959 (2016) - [i4]Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar:
Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes. CoRR abs/1610.08853 (2016) - [i3]Jinsung Yoon, Ahmed M. Alaa, Martin Cadeiras, Mihaela van der Schaar:
Personalized Donor-Recipient Matching for Organ Transplantation. CoRR abs/1611.03934 (2016) - [i2]Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar:
A Semi-Markov Switching Linear Gaussian Model for Censored Physiological Data. CoRR abs/1611.05146 (2016) - 2015
- [i1]Cem Tekin, Jinsung Yoon, Mihaela van der Schaar:
Adaptive Ensemble Learning with Confidence Bounds. CoRR abs/1512.07446 (2015)
Coauthor Index
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