48 citations · 119 across the 12 of their papers we have counts for
12 papers
Joint Learning of Network Topology and Opinion Dynamics Based on Bandit Algorithms
Yu Xing, Xudong Sun, Karl H. Johansson
We study joint learning of network topology and a mixed opinion dynamics, in which agents may have different update rules. Such a model captures the diversity of real individual in…
Proxy-Based Prediction of Solar Extreme Ultraviolet Emission using Deep Learning
Anthony L. Pineci, Peter Sadowski, Eric Gaidos +1
High-energy radiation from the Sun governs the behavior of Earth's upper atmosphere and such radiation from any planet-hosting star can drive the long-term evolution of a planetary…
Hierarchical Variational Auto-Encoding for Unsupervised Domain Generalization
Xudong Sun, Florian Buettner
We address the task of domain generalization, where the goal is to train a predictive model such that it is able to generalize to a new, previously unseen domain. We choose a hiera…
More Industry-friendly: Federated Learning with High Efficient Design
Dingwei Li, Qinglong Chang, Lixue Pang +4
Although many achievements have been made since Google threw out the paradigm of federated learning (FL), there still exists much room for researchers to optimize its efficiency. I…
Grid-GCN for Fast and Scalable Point Cloud Learning
Qiangeng Xu, Xudong Sun, Cho-Ying Wu +2
Due to the sparsity and irregularity of the point cloud data, methods that directly consume points have become popular. Among all point-based models, graph convolutional networks (…
Benchmarking time series classification -- Functional data vs machine learning approaches
Florian Pfisterer, Laura Beggel, Xudong Sun +2
Time series classification problems have drawn increasing attention in the machine learning and statistical community. Closely related is the field of functional data analysis (FDA…
Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning
Xudong Sun, Bernd Bischl
Aiming at a comprehensive and concise tutorial survey, recap of variational inference and reinforcement learning with Probabilistic Graphical Models are given with detailed derivat…
Variational Resampling Based Assessment of Deep Neural Networks under Distribution Shift
Xudong Sun, Alexej Gossmann, Yu Wang +1
A novel variational inference based resampling framework is proposed to evaluate the robustness and generalization capability of deep learning models with respect to distribution s…
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning
Rui Zhao, Xudong Sun, Volker Tresp
In Multi-Goal Reinforcement Learning, an agent learns to achieve multiple goals with a goal-conditioned policy. During learning, the agent first collects the trajectories into a re…
ReinBo: Machine Learning pipeline search and configuration with Bayesian Optimization embedded Reinforcement Learning
Xudong Sun, Jiali Lin, Bernd Bischl
Machine learning pipeline potentially consists of several stages of operations like data preprocessing, feature engineering and machine learning model training. Each operation has…
High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions
Xudong Sun, Andrea Bommert, Florian Pfisterer +3
A novel machine learning optimization process coined Restrictive Federated Model Selection (RFMS) is proposed under the scenario, for example, when data from healthcare units can n…
Face Detection using Deep Learning: An Improved Faster RCNN Approach
Xudong Sun, Pengcheng Wu, Steven C. H. Hoi
In this report, we present a new face detection scheme using deep learning and achieve the state-of-the-art detection performance on the well-known FDDB face detetion benchmark eva…