Search Results for author: Kun Yang

Found 22 papers, 2 papers with code

DMSA: Dynamic Multi-scale Unsupervised Semantic Segmentation Based on Adaptive Affinity

1 code implementation1 Mar 2023 Kun Yang, Jun Lu

The proposed method in this paper proposes an end-to-end unsupervised semantic segmentation architecture DMSA based on four loss functions.

Unsupervised Semantic Segmentation

A novel efficient Multi-view traffic-related object detection framework

no code implementations23 Feb 2023 Kun Yang, Jing Liu, Dingkang Yang, Hanqi Wang, Peng Sun, Yanni Zhang, Yan Liu, Liang Song

With the rapid development of intelligent transportation system applications, a tremendous amount of multi-view video data has emerged to enhance vehicle perception.

Model Selection object-detection +1

Orthogonal-Time-Frequency-Space Signal Design for Integrated Data and Energy Transfer: Benefits from Doppler Offsets

no code implementations3 Feb 2023 Jie Hu, Ke Xu, Luping Xiang, Kun Yang

Integrated data and energy transfer (IDET) is an advanced technology for enabling energy sustainability for massively deployed low-power electronic consumption components.

SISO-OFDM and MISO-OFDM Counterparts for "Wideband Waveforming for Integrated Data and Energy Transfer: Creating Extra Gain Beyond Multiple Antennas and Multiple Carriers"

no code implementations8 Dec 2022 Zhonglun Wang, Jie Hu, Kun Yang

In this article, we proposethe SISO-OFDM and MISO-OFDM based IDET systems, which are the counterparts of our optimal wideband waveforming strategy in [1].

QuatDE: Dynamic Quaternion Embedding for Knowledge Graph Completion

1 code implementation19 May 2021 Haipeng Gao, Kun Yang, Yuxue Yang, Rufai Yusuf Zakari, Jim Wilson Owusu, Ke Qin

Knowledge graph embedding has been an active research topic for knowledge base completion (KGC), with progressive improvement from the initial TransE, TransH, RotatE et al to the current state-of-the-art QuatE.

Knowledge Base Completion Knowledge Graph Completion +2

Connecting AI Learning and Blockchain Mining in 6G Systems

no code implementations29 Apr 2021 Yunkai Wei, Zixian An, Supeng Leng, Kun Yang

The sixth generation (6G) systems are generally recognized to be established on ubiquitous Artificial Intelligence (AI) and distributed ledger such as blockchain.

An Efficient One-Class SVM for Anomaly Detection in the Internet of Things

no code implementations22 Apr 2021 Kun Yang, Samory Kpotufe, Nick Feamster

Insecure Internet of things (IoT) devices pose significant threats to critical infrastructure and the Internet at large; detecting anomalous behavior from these devices remains of critical importance, but fast, efficient, accurate anomaly detection (also called "novelty detection") for these classes of devices remains elusive.

Anomaly Detection

End-to-End Jet Classification of Boosted Top Quarks with the CMS Open Data

no code implementations19 Apr 2021 Michael Andrews, Bjorn Burkle, Yi-fan Chen, Davide DiCroce, Sergei Gleyzer, Ulrich Heintz, Meenakshi Narain, Manfred Paulini, Nikolas Pervan, Yusef Shafi, Wei Sun, Emanuele Usai, Kun Yang

We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon.

Exactly solvable model of Fermi arcs and pseudogap

no code implementations3 Nov 2020 Kun Yang

We introduce a very simple and exactly solvable model that supports Fermi arcs in its ground state and excitation spectrum.

Strongly Correlated Electrons Superconductivity

6G Cellular Networks and Connected Autonomous Vehicles

no code implementations2 Oct 2020 Jianhua He, Kun Yang, Hsiao-Hwa Chen

With 5G mobile communication systems been commercially rolled out, research discussions on next generation mobile systems, i. e., 6G, have started.

Autonomous Vehicles

Feature Extraction for Novelty Detection in Network Traffic

no code implementations30 Jun 2020 Kun Yang, Samory Kpotufe, Nick Feamster

To facilitate such exploration, we develop a systematic framework, open-source toolkit, and public Python library that makes it both possible and easy to extract and generate features from network traffic and perform and end-to-end evaluation of these representations across most prevalent modern novelty detection models.

Anomaly Detection BIG-bench Machine Learning +1

Distributed Resource Scheduling for Large-Scale MEC Systems: A Multi-Agent Ensemble Deep Reinforcement Learning with Imitation Acceleration

no code implementations21 May 2020 Feibo Jiang, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan

We consider the optimization of distributed resource scheduling to minimize the sum of task latency and energy consumption for all the Internet of things devices (IoTDs) in a large-scale mobile edge computing (MEC) system.

Decision Making Edge-computing +1

AI Driven Heterogeneous MEC System with UAV Assistance for Dynamic Environment -- Challenges and Solutions

no code implementations11 Feb 2020 Feibo Jiang, Kezhi Wang, Li Dong, Cunhua Pan, Wei Xu, Kun Yang

By taking full advantage of Computing, Communication and Caching (3C) resources at the network edge, Mobile Edge Computing (MEC) is envisioned as one of the key enablers for the next generation networks.

Association Decision Making +4

Stacked Auto Encoder Based Deep Reinforcement Learning for Online Resource Scheduling in Large-Scale MEC Networks

no code implementations24 Jan 2020 Feibo Jiang, Kezhi Wang, Li Dong, Cunhua Pan, Kun Yang

An online resource scheduling framework is proposed for minimizing the sum of weighted task latency for all the Internet of things (IoT) users, by optimizing offloading decision, transmission power and resource allocation in the large-scale mobile edge computing (MEC) system.

Data Compression Edge-computing +1

RL-Based User Association and Resource Allocation for Multi-UAV enabled MEC

no code implementations8 Apr 2019 Liang Wang, Peiqiu Huang, Kezhi Wang, Guopeng Zhang, Lei Zhang, Nauman Aslam, Kun Yang

In this paper, multi-unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC), i. e., UAVE is studied, where several UAVs are deployed as flying MEC platform to provide computing resource to ground user equipments (UEs).

Association Edge-computing +1

Machine Learning in High Energy Physics Community White Paper

no code implementations8 Jul 2018 Kim Albertsson, Piero Altoe, Dustin Anderson, John Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano, Laurent Basara, Adrian Bevan, Wahid Bhimji, Daniele Bonacorsi, Bjorn Burkle, Paolo Calafiura, Mario Campanelli, Louis Capps, Federico Carminati, Stefano Carrazza, Yi-fan Chen, Taylor Childers, Yann Coadou, Elias Coniavitis, Kyle Cranmer, Claire David, Douglas Davis, Andrea De Simone, Javier Duarte, Martin Erdmann, Jonas Eschle, Amir Farbin, Matthew Feickert, Nuno Filipe Castro, Conor Fitzpatrick, Michele Floris, Alessandra Forti, Jordi Garra-Tico, Jochen Gemmler, Maria Girone, Paul Glaysher, Sergei Gleyzer, Vladimir Gligorov, Tobias Golling, Jonas Graw, Lindsey Gray, Dick Greenwood, Thomas Hacker, John Harvey, Benedikt Hegner, Lukas Heinrich, Ulrich Heintz, Ben Hooberman, Johannes Junggeburth, Michael Kagan, Meghan Kane, Konstantin Kanishchev, Przemysław Karpiński, Zahari Kassabov, Gaurav Kaul, Dorian Kcira, Thomas Keck, Alexei Klimentov, Jim Kowalkowski, Luke Kreczko, Alexander Kurepin, Rob Kutschke, Valentin Kuznetsov, Nicolas Köhler, Igor Lakomov, Kevin Lannon, Mario Lassnig, Antonio Limosani, Gilles Louppe, Aashrita Mangu, Pere Mato, Narain Meenakshi, Helge Meinhard, Dario Menasce, Lorenzo Moneta, Seth Moortgat, Mark Neubauer, Harvey Newman, Sydney Otten, Hans Pabst, Michela Paganini, Manfred Paulini, Gabriel Perdue, Uzziel Perez, Attilio Picazio, Jim Pivarski, Harrison Prosper, Fernanda Psihas, Alexander Radovic, Ryan Reece, Aurelius Rinkevicius, Eduardo Rodrigues, Jamal Rorie, David Rousseau, Aaron Sauers, Steven Schramm, Ariel Schwartzman, Horst Severini, Paul Seyfert, Filip Siroky, Konstantin Skazytkin, Mike Sokoloff, Graeme Stewart, Bob Stienen, Ian Stockdale, Giles Strong, Wei Sun, Savannah Thais, Karen Tomko, Eli Upfal, Emanuele Usai, Andrey Ustyuzhanin, Martin Vala, Justin Vasel, Sofia Vallecorsa, Mauro Verzetti, Xavier Vilasís-Cardona, Jean-Roch Vlimant, Ilija Vukotic, Sean-Jiun Wang, Gordon Watts, Michael Williams, Wenjing Wu, Stefan Wunsch, Kun Yang, Omar Zapata

In this document we discuss promising future research and development areas for machine learning in particle physics.

BIG-bench Machine Learning

Point Set Registration With Global-Local Correspondence and Transformation Estimation

no code implementations ICCV 2017 Su Zhang, Yang Yang, Kun Yang, Yi Luo, Sim-Heng Ong

We present a new point set registration method with global-local correspondence and transformation estimation (GL-CATE).

Density Estimation via Discrepancy

no code implementations23 Sep 2015 Kun Yang, Hao Su, Wing Hung Wang

Given i. i. d samples from some unknown continuous density on hyper-rectangle $[0, 1]^d$, we attempt to learn a piecewise constant function that approximates this underlying density non-parametrically.

Density Estimation

Density Estimation via Discrepancy Based Adaptive Sequential Partition

no code implementations NeurIPS 2016 Dangna Li, Kun Yang, Wing Hung Wong

Given $iid$ observations from an unknown absolute continuous distribution defined on some domain $\Omega$, we propose a nonparametric method to learn a piecewise constant function to approximate the underlying probability density function.

Density Estimation

Cannot find the paper you are looking for? You can Submit a new open access paper.