1 code implementation • 21 Mar 2024 • 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 is a modular Python package for training user specified neural networks with composable regularization loss terms.
1 code implementation • 20 Mar 2024 • Xudong Sun, Nutan Chen, Alexej Gossmann, Yu Xing, Carla Feistner, Emilio Dorigatt, Felix Drost, Daniele Scarcella, Lisa Beer, Carsten Marr
We address the online combinatorial choice of weight multipliers for multi-objective optimization of many loss terms parameterized by neural works via a probabilistic graphical model (PGM) for the joint model parameter and multiplier evolution process, with a hypervolume based likelihood promoting multi-objective descent.
no code implementations • 25 Jun 2023 • 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.
1 code implementation • 4 Oct 2022 • Muhammad Umar B. Niazi, John Cao, Xudong Sun, Amritam Das, Karl Henrik Johansson
Designing Luenberger observers for nonlinear systems involves the challenging task of transforming the state to an alternate coordinate system, possibly of higher dimensions, where the system is asymptotically stable and linear up to output injection.
no code implementations • 23 Jan 2021 • 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.
no code implementations • 16 Dec 2020 • Dingwei Li, Qinglong Chang, Lixue Pang, Yanfang Zhang, Xudong Sun, Jikun Ding, Liang Zhang
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.
1 code implementation • CVPR 2020 • Qiangeng Xu, Xudong Sun, Cho-Ying Wu, Panqu Wang, Ulrich Neumann
Compared with popular sampling methods such as Farthest Point Sampling (FPS) and Ball Query, CAGQ achieves up to 50X speed-up.
1 code implementation • 18 Nov 2019 • Florian Pfisterer, Laura Beggel, Xudong Sun, Fabian Scheipl, Bernd Bischl
In order to assess the methods and implementations, we run a benchmark on a wide variety of representative (time series) data sets, with in-depth analysis of empirical results, and strive to provide a reference ranking for which method(s) to use for non-expert practitioners.
no code implementations • 25 Aug 2019 • 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 derivations.
1 code implementation • 7 Jun 2019 • Xudong Sun, Alexej Gossmann, Yu Wang, Bernd Bischl
A novel variational inference based resampling framework is proposed to evaluate the robustness and generalization capability of deep learning models with respect to distribution shift.
3 code implementations • 21 May 2019 • Rui Zhao, Xudong Sun, Volker Tresp
This objective encourages the agent to maximize the expected return, as well as to achieve more diverse goals.
1 code implementation • 10 Apr 2019 • 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.
1 code implementation • 24 Feb 2019 • Xudong Sun, Andrea Bommert, Florian Pfisterer, Jörg Rahnenführer, Michel Lang, Bernd Bischl
To carry out a clinical research under this scenario, an analyst could train a machine learning model only on local data site, but it is still possible to execute a statistical query at a certain cost in the form of sending a machine learning model to some of the remote data sites and get the performance measures as feedback, maybe due to prediction being usually much cheaper.
no code implementations • 12 Jan 2018 • Xudong Sun
This document provides some technical notes on the polar field correction scheme for the HMI synoptic maps and daily updated synchronic frames.
Solar and Stellar Astrophysics
no code implementations • 28 Jan 2017 • 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 evaluation.
1 code implementation • 10 Sep 2013 • Xudong Sun
We describe the coordinate systems of two streams of HMI active region vector data.
Solar and Stellar Astrophysics Instrumentation and Methods for Astrophysics