Xudong Sun - RankMe

25 papers A* 1A 1C 2Journal 13Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Addressing pitfalls in implicit unobserved confounding synthesis using explicit block hierarchical ancestral sampling. CoRR Xudong Sun, Alex Markham, Pratik Misra, Carsten Marr
2025	A	`conf`	M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling. AISTATS Xudong Sun, Nutan Chen, Alexej Gossmann, Yu Xing, Matteo Wohlrapp, Emilio Dorigatti, Carla Feistner, Felix Drost, Daniele Scarcella, Lisa Beer, Carsten Marr
2024	J	`jnl`	DomainLab: A modular Python package for domain generalization in deep learning. CoRR 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
2024	J	`jnl`	M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling. CoRR Xudong Sun, Nutan Chen, Alexej Gossmann, Yu Xing, Carla Feistner, Emilio Dorigatt, Felix Drost, Daniele Scarcella, Lisa Beer, Carsten Marr
2023	—	`conf`	Deep Unsupervised Clustering for Conditional Identification of Subgroups Within a Digital Pathology Image Set. MICCAI (8) Mariia Sidulova, Xudong Sun, Alexej Gossmann
2023	J	`jnl`	Joint Learning of Network Topology and Opinion Dynamics Based on Bandit Algorithms. CoRR Yu Xing, Xudong Sun, Karl Henrik Johansson
2023	C	`conf`	Learning-based Design of Luenberger Observers for Autonomous Nonlinear Systems. ACC Muhammad Umar B. Niazi, John Cao, Xudong Sun, Amritam Das, Karl Henrik Johansson
2022	J	`jnl`	Learning-based Design of Luenberger Observers for Autonomous Nonlinear Systems. CoRR Muhammad Umar B. Niazi, John Cao, Xudong Sun, Amritam Das, Karl Henrik Johansson
2021	—	`—`	Machine learning model selection with multi-objective Bayesian optimization and reinforcement learning: case studies on functional data analysis, pipeline tuning and shifted distribution. Xudong Sun
2020	J	`jnl`	Benchmark for filter methods for feature selection in high-dimensional classification data. Comput. Stat. Data Anal. Andrea Bommert, Xudong Sun, Bernd Bischl, Jörg Rahnenführer, Michel Lang
2020	—	`conf`	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 Alexej Gossmann, Kenny H. Cha, Xudong Sun
2019	J	`jnl`	Benchmarking time series classification - Functional data vs machine learning approaches. CoRR Florian Pfisterer, Laura Beggel, Xudong Sun, Fabian Scheipl, Bernd Bischl
2019	—	`conf`	High Dimensional Restrictive Federated Model Selection with Multi-objective Bayesian Optimization over Shifted Distributions. IntelliSys (1) Xudong Sun, Andrea Bommert, Florian Pfisterer, Jörg Rahnenführer, Michel Lang, Bernd Bischl
2019	J	`jnl`	High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions. CoRR Xudong Sun, Andrea Bommert, Florian Pfisterer, Jörg Rahnenführer, Michel Lang, Bernd Bischl
2019	A*	`conf`	Maximum Entropy-Regularized Multi-Goal Reinforcement Learning. ICML Rui Zhao, Xudong Sun, Volker Tresp
2019	J	`jnl`	Maximum Entropy-Regularized Multi-Goal Reinforcement Learning. CoRR Rui Zhao, Xudong Sun, Volker Tresp
2019	—	`conf`	ReinBo: Machine Learning Pipeline Conditional Hierarchy Search and Configuration with Bayesian Optimization Embedded Reinforcement Learning. PKDD/ECML Workshops (1) Xudong Sun, Jiali Lin, Bernd Bischl
2019	J	`jnl`	ReinBo: Machine Learning pipeline search and configuration with Bayesian Optimization embedded Reinforcement Learning. CoRR Xudong Sun, Jiali Lin, Bernd Bischl
2019	J	`jnl`	Resampling-based Assessment of Robustness to Distribution Shift for Deep Neural Networks. CoRR Xudong Sun, Yu Wang, Alexej Gossmann, Bernd Bischl
2019	—	`conf`	Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning. SSCI Xudong Sun, Bernd Bischl
2019	J	`jnl`	Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning. CoRR Xudong Sun, Bernd Bischl
2019	—	`conf`	Variational Resampling Based Assessment of Deep Neural Networks under Distribution Shift. SSCI Xudong Sun, Alexej Gossmann, Yu Wang, Bernd Bischl
2018	J	`jnl`	A Lesson learned from PMF based approach for Semantic Recommender System. J. Intell. Inf. Syst. Nidhi Kushwaha, Xudong Sun, Bharat Singh, O. P. Vyas
2017	C	`conf`	First Investigations on Noisy Model-Based Multi-objective Optimization. EMO Daniel Horn, Melanie Dagge, Xudong Sun, Bernd Bischl
2016	—	`conf`	SemPMF: Semantic Inclusion by Probabilistic Matrix Factorization for Recommender System. PAAMS (Special Sessions) Nidhi Kushwaha, Xudong Sun, O. P. Vyas, Artus Krohn-Grimberghe