Xudong Sun

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 19

Top Topics

Variational Inference

Maximum Entropy

Feature Selection

Reinforcement Learning

Top Venues

Medical Imaging: Computer-Aided Diagnosis

Publications

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 (2024)
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 (2024)
Mariia Sidulova, Xudong Sun, Alexej Gossmann
Deep Unsupervised Clustering for Conditional Identification of Subgroups Within a Digital Pathology Image Set. MICCAI (8) (2023)
Andrea Bommert, Xudong Sun, Bernd Bischl, Jörg Rahnenführer, Michel Lang
Benchmark for filter methods for feature selection in high-dimensional classification data. Comput. Stat. Data Anal. 143 (2020)
Alexej Gossmann, Kenny H. Cha, Xudong Sun
Performance deterioration of deep neural networks for lesion classification in mammography due to distribution shift: an analysis based on artificially created distribution shift. Medical Imaging: Computer-Aided Diagnosis (2020)
Rui Zhao, Xudong Sun, Volker Tresp
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning. CoRR (2019)
Florian Pfisterer, Laura Beggel, Xudong Sun, Fabian Scheipl, Bernd Bischl
Benchmarking time series classification - Functional data vs machine learning approaches. CoRR (2019)
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 (2019)
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. IntelliSys (1) (2019)
Xudong Sun, Bernd Bischl
Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning. CoRR (2019)
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)
Xudong Sun, Jiali Lin, Bernd Bischl
ReinBo: Machine Learning pipeline search and configuration with Bayesian Optimization embedded Reinforcement Learning. CoRR (2019)
Xudong Sun, Yu Wang, Alexej Gossmann, Bernd Bischl
Resampling-based Assessment of Robustness to Distribution Shift for Deep Neural Networks. CoRR (2019)
Xudong Sun, Alexej Gossmann, Yu Wang, Bernd Bischl
Variational Resampling Based Assessment of Deep Neural Networks under Distribution Shift. SSCI (2019)
Xudong Sun, Bernd Bischl
Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning. SSCI (2019)
Rui Zhao, Xudong Sun, Volker Tresp
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning. ICML (2019)
Nidhi Kushwaha, Xudong Sun, Bharat Singh, O. P. Vyas
A Lesson learned from PMF based approach for Semantic Recommender System. J. Intell. Inf. Syst. 50 (3) (2018)
Daniel Horn, Melanie Dagge, Xudong Sun, Bernd Bischl
First Investigations on Noisy Model-Based Multi-objective Optimization. EMO (2017)
Nidhi Kushwaha, Xudong Sun, O. P. Vyas, Artus Krohn-Grimberghe
SemPMF: Semantic Inclusion by Probabilistic Matrix Factorization for Recommender System. PAAMS (Special Sessions) (2016)