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Xudong Sun 0002
Person information
- affiliation: KTH Royal Institute of Technology, Stockholm, Sweden
- affiliation (PhD 2019): LMU Munich, Germany
Other persons with the same name
- Xudong Sun 0001 (aka: Xu-Dong Sun 0001) — Chinese Academy of Sciences, Institute of Automation, Beijing, China
- Xudong Sun 0003 — Tsinghua University, Department of Electrical Engineering, Beijing, China
- Xudong Sun 0004
— Shenzhen University, Shenzhen, China
- Xudong Sun 0005 — DeepIR Inc.
- Xudong Sun 0006 — Liaoning Technical University, Institute of Mathematics and Systems Science, China
- Xudong Sun 0007
- Xudong Sun 0008 — Hohai University, College of Science, Nanjing, China
- Xudong Sun 0009
- Xudong Sun 0010 — Nanjing University of Information Science and Technology, Jiangsu Key Laboratory of Big Data Analysis Technology, China
- Xu-Dong Sun 0011 (aka: Xudong Sun 0011) — Hebei University of Technology, School of Electronic and Information Engineering, Tianjin, China
- Xudong Sun 0012 — Huawei Technologies Co., Ltd, China
- Xudong Sun 0013
- Xudong Sun 0014 — Siemens AG
- Xudong Sun 0015 — Xidian University, School of Mechano-Electronic Engineering, Xi'an, China
- Xudong Sun 0016 — North China University of Science and Technology, Department of Mechanical Engineering, Tangshan, China
- Xudong Sun 0017 — Beijing University of Technology, College of Microelectronics, China
- Xudong Sun 0018 — Shijiazhuang Tiedao University, Department of Mathematics and Physics, China
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2020 – today
- 2024
- [i10]Xudong Sun, Nutan Chen, Alexej Gossmann, Yu Xing, Carla Feistner, Emilio Dorigatt, Felix Drost, Daniele Scarcella, Lisa Beer, Carsten Marr:
M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling. CoRR abs/2403.13728 (2024) - [i9]Xudong Sun, Carla Feistner, Alexej Gossmann, George Schwarz, Rao Muhammad Umer, Lisa Beer, Patrick Rockenschaub, Rahul Babu Shrestha, Armin Gruber, Nutan Chen, Sayedali Shetab Boushehri, Florian Buettner, Carsten Marr:
DomainLab: A modular Python package for domain generalization in deep learning. CoRR abs/2403.14356 (2024) - 2023
- [c10]Muhammad Umar B. Niazi, John Cao, Xudong Sun, Amritam Das, Karl Henrik Johansson:
Learning-based Design of Luenberger Observers for Autonomous Nonlinear Systems. ACC 2023: 3048-3055 - [c9]Mariia Sidulova
Deep Unsupervised Clustering for Conditional Identification of Subgroups Within a Digital Pathology Image Set. MICCAI (8) 2023: 666-675 - [i8]Yu Xing, Xudong Sun, Karl Henrik Johansson:
Joint Learning of Network Topology and Opinion Dynamics Based on Bandit Algorithms. CoRR abs/2306.15695 (2023) - 2022
- [i7]Muhammad Umar B. Niazi, John Cao, Xudong Sun, Amritam Das, Karl Henrik Johansson:
Learning-based Design of Luenberger Observers for Autonomous Nonlinear Systems. CoRR abs/2210.01476 (2022) - 2021
- [b1]Xudong Sun:
Machine learning model selection with multi-objective Bayesian optimization and reinforcement learning: case studies on functional data analysis, pipeline tuning and shifted distribution. Ludwig Maximilian University of Munich, Germany, 2021 - 2020
- [j2]Andrea Bommert
Benchmark for filter methods for feature selection in high-dimensional classification data. Comput. Stat. Data Anal. 143 (2020) - [c8]Alexej Gossmann
Performance deterioration of deep neural networks for lesion classification in mammography due to distribution shift: an analysis based on artificially created distribution shift. Computer-Aided Diagnosis 2020
2010 – 2019
- 2019
- [c7]Rui Zhao, Xudong Sun, Volker Tresp:
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning. ICML 2019: 7553-7562 - [c6]Xudong Sun, Andrea Bommert
High Dimensional Restrictive Federated Model Selection with Multi-objective Bayesian Optimization over Shifted Distributions. IntelliSys (1) 2019: 629-647 - [c5]Xudong Sun, Jiali Lin, Bernd Bischl:
ReinBo: Machine Learning Pipeline Conditional Hierarchy Search and Configuration with Bayesian Optimization Embedded Reinforcement Learning. PKDD/ECML Workshops (1) 2019: 68-84 - [c4]Xudong Sun, Bernd Bischl:
Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning. SSCI 2019: 110-119 - [c3]Xudong Sun, Alexej Gossmann
Variational Resampling Based Assessment of Deep Neural Networks under Distribution Shift. SSCI 2019: 1344-1353 - [i6]Xudong Sun, Andrea Bommert, Florian Pfisterer, Jörg Rahnenführer, Michel Lang, Bernd Bischl:
High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions. CoRR abs/1902.08999 (2019) - [i5]Xudong Sun, Jiali Lin, Bernd Bischl:
ReinBo: Machine Learning pipeline search and configuration with Bayesian Optimization embedded Reinforcement Learning. CoRR abs/1904.05381 (2019) - [i4]Rui Zhao, Xudong Sun, Volker Tresp:
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning. CoRR abs/1905.08786 (2019) - [i3]Xudong Sun, Yu Wang, Alexej Gossmann, Bernd Bischl:
Resampling-based Assessment of Robustness to Distribution Shift for Deep Neural Networks. CoRR abs/1906.02972 (2019) - [i2]Xudong Sun, Bernd Bischl:
Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning. CoRR abs/1908.09381 (2019) - [i1]Florian Pfisterer, Laura Beggel, Xudong Sun, Fabian Scheipl, Bernd Bischl:
Benchmarking time series classification - Functional data vs machine learning approaches. CoRR abs/1911.07511 (2019) - 2018
- [j1]Nidhi Kushwaha
A Lesson learned from PMF based approach for Semantic Recommender System. J. Intell. Inf. Syst. 50(3): 441-453 (2018) - 2017
- [c2]Daniel Horn, Melanie Dagge
First Investigations on Noisy Model-Based Multi-objective Optimization. EMO 2017: 298-313 - 2016
- [c1]Nidhi Kushwaha
SemPMF: Semantic Inclusion by Probabilistic Matrix Factorization for Recommender System. PAAMS (Special Sessions) 2016: 327-334
Coauthor Index
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last updated on 2024-12-10 21:42 CET by the dblp team
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