no code implementations • LREC 2022 • Xinyuan Xia, Lu Xiao, Kun Yang, Yueyue Wang
Our CS/CM annotated interview corpus is openly accessible.
no code implementations • 3 May 2024 • Yichun Tai, Kun Yang, Tao Peng, Zhenzhen Huang, Zhijiang Zhang
To this end, we propose Stable Surface Defect Generation (StableSDG), which transfers the vast generation distribution embedded in Stable Diffusion model for steel surface defect image generation.
no code implementations • 25 Apr 2024 • Mingcheng Li, Dingkang Yang, Xiao Zhao, Shuaibing Wang, Yan Wang, Kun Yang, Mingyang Sun, Dongliang Kou, Ziyun Qian, Lihua Zhang
Specifically, we present a sample-level contrastive distillation mechanism that transfers comprehensive knowledge containing cross-sample correlations to reconstruct missing semantics.
no code implementations • 20 Apr 2024 • Feibo Jiang, Li Dong, Siwei Tu, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Dusit Niyato
Large Language Models (LLMs) have revolutionized natural language processing tasks.
no code implementations • 9 Mar 2024 • Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You
Semantic Communication (SC) is a novel paradigm for data transmission in 6G.
no code implementations • 9 Mar 2024 • Dingkang Yang, Kun Yang, Mingcheng Li, Shunli Wang, Shuaibing Wang, Lihua Zhang
Following the causal graph, CLEF introduces a non-invasive context branch to capture the adverse direct effect caused by the context bias.
no code implementations • 8 Mar 2024 • Dingkang Yang, Mingcheng Li, Dongling Xiao, Yang Liu, Kun Yang, Zhaoyu Chen, Yuzheng Wang, Peng Zhai, Ke Li, Lihua Zhang
In the inference phase, given a factual multimodal input, MCIS imagines two counterfactual scenarios to purify and mitigate these biases.
no code implementations • 8 Mar 2024 • Xingran Chen, Yusha Liu, Yali Zheng, Kun Yang
In this letter, we introduce the novel concept, Age of Computing (AoC), to capture computation freshness in 3CNs.
1 code implementation • 15 Feb 2024 • Chengshuai Shi, Kun Yang, Jing Yang, Cong Shen
Based on this connection, a general framework TRIPLE (besT aRm Identification for Prompt LEarning) is proposed to harness the power of BAI-FB in prompt learning systematically.
no code implementations • 26 Dec 2023 • Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen
Federated learning (FL) has demonstrated great potential in revolutionizing distributed machine learning, and tremendous efforts have been made to extend it beyond the original focus on supervised learning.
no code implementations • 16 Dec 2023 • Kun Yang, Shu-ping Yeh, Menglei Zhang, Jerry Sydir, Jing Yang, Cong Shen
Dynamic radio resource management (RRM) in wireless networks presents significant challenges, particularly in the context of Radio Access Network (RAN) slicing.
no code implementations • 13 Dec 2023 • Feibo Jiang, Li Dong, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Dusit Niyato, Octavia A. Dobre
The rapid development of the Large Language Model (LLM) presents huge opportunities for 6G communications, e. g., network optimization and management by allowing users to input task requirements to LLMs by nature language.
1 code implementation • 7 Dec 2023 • Guoqing Yang, Zhiming Luo, Jianzhe Gao, Yingxin Lai, Kun Yang, Yifan He, Shaozi Li
Human behavior anomaly detection aims to identify unusual human actions, playing a crucial role in intelligent surveillance and other areas.
no code implementations • 19 Nov 2023 • Kun Yang, Cong Shen, Jing Yang, Shu-ping Yeh, Jerry Sydir
We observe that the performance of offline RL for the RRM problem depends critically on the behavior policy used for data collection, and further propose a novel offline RL solution that leverages heterogeneous datasets collected by different behavior policies.
no code implementations • 15 Nov 2023 • Cheng Luo, Jie Hu, Luping Xiang, Kun Yang, Kai-Kit Wong
Intelligent Reflecting Surface (IRS) utilizes low-cost, passive reflecting elements to enhance the passive beam gain, improve Wireless Energy Transfer (WET) efficiency, and enable its deployment for numerous Internet of Things (IoT) devices.
no code implementations • 21 Oct 2023 • Luping Xiang, Ke Xu, Jie Hu, Christos Masouros, Kun Yang
This paper proposes a novel non-orthogonal multiple access (NOMA)-assisted orthogonal time-frequency space (OTFS)-integrated sensing and communication (ISAC) network, which uses unmanned aerial vehicles (UAVs) as air base stations to support multiple users.
no code implementations • 21 Oct 2023 • Luping Xiang, Ke Xu, Jie Hu, Kun Yang
In this paper, we propose a green beamforming design for the integrated sensing and communication (ISAC) system, using beam-matching error to assess radar performance.
no code implementations • 3 Sep 2023 • Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You
To this end, we propose a Large AI Model-based Multimodal SC (LAM-MSC) framework, in which we first present the MLM-based Multimodal Alignment (MMA) that utilizes the MLM to enable the transformation between multimodal and unimodal data while preserving semantic consistency.
no code implementations • 29 Aug 2023 • Li Dong, Feibo Jiang, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Robert Schober
Next-generation edge intelligence is anticipated to bring huge benefits to various applications, e. g., offloading systems.
1 code implementation • ICCV 2023 • Dingkang Yang, Shuai Huang, Zhi Xu, Zhenpeng Li, Shunli Wang, Mingcheng Li, Yuzheng Wang, Yang Liu, Kun Yang, Zhaoyu Chen, Yan Wang, Jing Liu, Peixuan Zhang, Peng Zhai, Lihua Zhang
Driver distraction has become a significant cause of severe traffic accidents over the past decade.
1 code implementation • ICCV 2023 • Kun Yang, Dingkang Yang, Jingyu Zhang, Mingcheng Li, Yang Liu, Jing Liu, Hanqi Wang, Peng Sun, Liang Song
In this paper, we propose SCOPE, a novel collaborative perception framework that aggregates the spatio-temporal awareness characteristics across on-road agents in an end-to-end manner.
no code implementations • 21 Jul 2023 • Yao Wen, Guopeng Zhang, Kezhi Wang, Kun Yang
To alleviate the shortage of computing power faced by clients in training deep neural networks (DNNs) using federated learning (FL), we leverage the edge computing and split learning to propose a model-splitting allowed FL (SFL) framework, with the aim to minimize the training latency without loss of test accuracy.
no code implementations • 7 Jul 2023 • Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You
Semantic communication (SC) is an emerging intelligent paradigm, offering solutions for various future applications like metaverse, mixed-reality, and the Internet of everything.
no code implementations • 16 Jun 2023 • Soham Jana, Kun Yang, Sanjeev Kulkarni
In the absence of outliers, in fixed dimensions, our theoretical guarantees are similar to that of the Lloyd algorithm.
1 code implementation • 1 Jun 2023 • Zhixu Tao, Kun Yang, Sanjeev R. Kulkarni
This paper focuses on the problem of adversarial attacks from Byzantine machines in a Federated Learning setting where non-Byzantine machines can be partitioned into disjoint clusters.
no code implementations • 10 Apr 2023 • Jieming Bian, Lei Wang, Kun Yang, Cong Shen, Jie Xu
In this paper, we provide theoretical analysis of hybrid FL under clients' partial participation to validate that partial participation is the key constraint on convergence speed.
1 code implementation • 1 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.
no code implementations • 23 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.
no code implementations • 3 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.
no code implementations • 8 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].
2 code implementations • IEEE Transactions on Medical Imaging 2022 • Mufeng Geng, Xiangxi Meng, Jiangyuan Yu, Lei Zhu, Lujia Jin, Zhe Jiang, Bin Qiu, Hui Li, Hanjing Kong, Jianmin Yuan, Kun Yang, Hongming Shan, Hongbin Han, Zhi Yang, Qiushi Ren, Yanye Lu
In this study, we propose a simple yet effective strategy, the content-noise complementary learning (CNCL) strategy, in which two deep learning predictors are used to learn the respective content and noise of the image dataset complementarily.
1 code implementation • 19 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.
Ranked #2 on Link Prediction on WN18
no code implementations • 29 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.
no code implementations • 22 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.
no code implementations • 19 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.
no code implementations • 3 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
no code implementations • 2 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.
no code implementations • 30 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.
no code implementations • 21 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.
no code implementations • JOURNAL OF COMMUNICATIONS AND NETWORKS 2020 • Wenli Ning, Xiaoyan Huang, Kun Yang, Fan Wu, and Supeng Leng
In cognitive radio (CR) networks, fast and accurate spectrum sensing plays a fundamental role in achieving high spectral efficiency.
no code implementations • 11 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.
no code implementations • 24 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.
no code implementations • 8 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).
no code implementations • 8 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 Vocal Bursts Intensity Prediction
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).
no code implementations • 23 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.
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.
no code implementations • 28 Jun 2013 • Kun Yang
Key words: penalized linear regression, lasso, elastic-net, ridge, MapReduce