no code implementations • 9 May 2024 • Siyuan Li, Xi Lin, Yaju Liu, Jianhua Li
We believe that TrustGAIN is a necessary paradigm for intelligent and trustworthy 6G networks to support AIGC services, ensuring the security, privacy, and fairness of AIGC network services.
no code implementations • 5 May 2024 • Siyuan Li, Xi Lin, Hansong Xu, Kun Hua, Xiaomin Jin, Gaolei Li, Jianhua Li
In this paper, we focus on the edge optimization of AIGC task execution and propose GMEL, a generative model-driven industrial AIGC collaborative edge learning framework.
no code implementations • 3 May 2024 • Changliang Zhou, Xi Lin, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang
The neural combinatorial optimization (NCO) approach has shown great potential for solving routing problems without the requirement of expert knowledge.
no code implementations • 30 Mar 2024 • Ping Guo, Qingfu Zhang, Xi Lin
In many real-world applications, the Pareto Set (PS) of a continuous multiobjective optimization problem can be a piecewise continuous manifold.
no code implementations • 28 Mar 2024 • Fu Luo, Xi Lin, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang
The end-to-end neural combinatorial optimization (NCO) method shows promising performance in solving complex combinatorial optimization problems without the need for expert design.
no code implementations • 27 Mar 2024 • Hanqing Fu, Gaolei Li, Jun Wu, Jianhua Li, Xi Lin, Kai Zhou, Yuchen Liu
Federated neuromorphic learning (FedNL) leverages event-driven spiking neural networks and federated learning frameworks to effectively execute intelligent analysis tasks over amounts of distributed low-power devices but also perform vulnerability to poisoning attacks.
1 code implementation • 15 Mar 2024 • Wanfang Su, Lixing Chen, Yang Bai, Xi Lin, Gaolei Li, Zhe Qu, Pan Zhou
The core philosophy of CMiMC is to preserve discriminative information of individual views in the collaborative view by maximizing mutual information between pre- and post-collaboration features while enhancing the efficacy of collaborative views by minimizing the loss function of downstream tasks.
no code implementations • 8 Mar 2024 • Ping Guo, Cheng Gong, Xi Lin, Zhiyuan Yang, Qingfu Zhang
To address this gap, we propose a new metric termed adversarial hypervolume, assessing the robustness of deep learning models comprehensively over a range of perturbation intensities from a multi-objective optimization standpoint.
no code implementations • 29 Feb 2024 • Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu, Zhenkun Wang, Qingfu Zhang
Multi-objective optimization problems can be found in many real-world applications, where the objectives often conflict each other and cannot be optimized by a single solution.
no code implementations • 28 Feb 2024 • Ke Xue, Xi Lin, Yunqi Shi, Shixiong Kai, Siyuan Xu, Chao Qian
Placement is crucial in the physical design, as it greatly affects power, performance, and area metrics.
1 code implementation • 23 Feb 2024 • Fei Liu, Xi Lin, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan
The results show that the unified model demonstrates superior performance in the eleven VRPs, reducing the average gap to around 5% from over 20% in the existing approach and achieving a significant performance boost on benchmark datasets as well as a real-world logistics application.
no code implementations • 14 Feb 2024 • Xiaoyuan Zhang, Xi Lin, Qingfu Zhang
It is desirable in many multi-objective machine learning applications, such as multi-task learning with conflicting objectives and multi-objective reinforcement learning, to find a Pareto solution that can match a given preference of a decision maker.
Multi-Objective Reinforcement Learning Multi-Task Learning +1
no code implementations • 14 Feb 2024 • Xiaoyuan Zhang, Xi Lin, Yichi Zhang, Yifan Chen, Qingfu Zhang
Multiobjective optimization (MOO) is prevalent in numerous applications, in which a Pareto front (PF) is constructed to display optima under various preferences.
2 code implementations • 27 Jan 2024 • Ping Guo, Fei Liu, Xi Lin, Qingchuan Zhao, Qingfu Zhang
In the rapidly evolving field of machine learning, adversarial attacks present a significant challenge to model robustness and security.
no code implementations • 19 Jan 2024 • Ping Guo, Zhiyuan Yang, Xi Lin, Qingchuan Zhao, Qingfu Zhang
Black-box query-based attacks constitute significant threats to Machine Learning as a Service (MLaaS) systems since they can generate adversarial examples without accessing the target model's architecture and parameters.
3 code implementations • 4 Jan 2024 • Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang
Heuristics are indispensable for tackling complex search and optimization problems.
no code implementations • 30 Nov 2023 • Kangkang Sun, Xiaojin Zhang, Xi Lin, Gaolei Li, Jing Wang, Jianhua Li
Researchers have struggled to design fair FL systems that ensure fairness of results.
no code implementations • 31 Oct 2023 • Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Qingfu Zhang
In this work, we make the first attempt to incorporate the structure constraints into the whole solution set by a single Pareto set model, which can be efficiently learned by a simple evolutionary stochastic optimization method.
1 code implementation • 19 Oct 2023 • Fei Liu, Xi Lin, Zhenkun Wang, Shunyu Yao, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang
It is also promising to see the operator only learned from a few instances can have robust generalization performance on unseen problems with quite different patterns and settings.
no code implementations • 13 Oct 2023 • Chang Gao, Xi Lin, Fang He, Xindi Tang
This study proposes an innovative model-based modular approach (MMA) to dynamically optimize order matching and vehicle relocation in a ride-hailing platform.
1 code implementation • NeurIPS 2023 • Fu Luo, Xi Lin, Fei Liu, Qingfu Zhang, Zhenkun Wang
Neural combinatorial optimization (NCO) is a promising learning-based approach for solving challenging combinatorial optimization problems without specialized algorithm design by experts.
no code implementations • 9 Aug 2023 • Yuxin Qi, Xi Lin, Jun Wu
We propose NAP-GNN, a node-importance-grained privacy-preserving GNN algorithm with privacy guarantees based on adaptive differential privacy to safeguard node information.
1 code implementation • 24 Jul 2023 • Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang
Homotopy optimization is a traditional method to deal with a complicated optimization problem by solving a sequence of easy-to-hard surrogate subproblems.
no code implementations • 13 Jul 2023 • Jinhua Si, Fang He, Xi Lin, Xindi Tang
The integrated development of city clusters has given rise to an increasing demand for intercity travel.
no code implementations • 3 Feb 2023 • Lingfei Luan, Xi Lin, Wenbiao Li
The ultimate objective of this study is to instigate a scholarly discourse on the interplay between technological advancements in education and the evolution of human learning patterns, raising the question of whether technology is driving human evolution or vice versa.
1 code implementation • 16 Oct 2022 • Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang
This work represents the first attempt to model the Pareto set for expensive multi-objective optimization.
1 code implementation • 29 Mar 2022 • Xi Lin, Zhiyuan Yang, Qingfu Zhang
In this work, we generalize the idea of neural combinatorial optimization, and develop a learning-based approach to approximate the whole Pareto set for a given MOCO problem without further search procedure.
no code implementations • 8 Nov 2021 • Jianfei Guo, Zhiyuan Yang, Xi Lin, Qingfu Zhang
By representing object instances within the same category as shape and appearance variation of a shared NeRF template, our proposed method can achieve dense shape correspondences reasoning on images for a wide range of object classes.
no code implementations • ICLR 2022 • Xi Lin, Zhiyuan Yang, Qingfu Zhang
In this work, we generalize the idea of neural combinatorial optimization, and develop a learning-based approach to approximate the whole Pareto set for a given MOCO problem without further search procedure.
no code implementations • 14 Feb 2021 • Xiaoyan Wang, Xi Lin, Meng Li
We call such a mobility market with AV renting options the "AV crowdsourcing market".
no code implementations • 27 Oct 2020 • Xiaoting Wang, Xiaozhe Wang, Hao Sheng, Xi Lin
The increasing uncertainty level caused by growing renewable energy sources (RES) and aging transmission networks poses a great challenge in the assessment of total transfer capability (TTC) and available transfer capability (ATC).
no code implementations • 23 Oct 2020 • Yang Ma, Jiasen Niu, Wenyu Xing, Yunyan Yao, Ranran Cai, Jirong Sun, X. C. Xie, Xi Lin, Wei Han
Superconductivity has been one of the most fascinating quantum states of matter for over several decades.
Superconductivity Mesoscale and Nanoscale Physics Materials Science
no code implementations • 13 Oct 2020 • Xi Lin, Zhiyuan Yang, Qingfu Zhang, Sam Kwong
With a fixed model capacity, the tasks would be conflicted with each other, and the system usually has to make a trade-off among learning all of them together.
no code implementations • 13 Feb 2020 • Ke Zhang, Meng Li, Zhengchao Zhang, Xi Lin, Fang He
Multi-vehicle routing problem with soft time windows (MVRPSTW) is an indispensable constituent in urban logistics distribution systems.
1 code implementation • NeurIPS 2019 • Xi Lin, Hui-Ling Zhen, Zhenhua Li, Qingfu Zhang, Sam Kwong
Recently, a novel method is proposed to find one single Pareto optimal solution with good trade-off among different tasks by casting multi-task learning as multiobjective optimization.
1 code implementation • 2 Dec 2019 • Xi Lin, Dingyi Sun, Tzu-Yuan Lin, Ryan M. Eustice, Maani Ghaffari
The experimental evaluations using publicly available RGB-D benchmarks show that the developed keyframe selection technique using continuous visual odometry outperforms its robust dense (and direct) visual odometry equivalent.
no code implementations • 4 Nov 2018 • Hui-Ling Zhen, Xi Lin, Alan Z. Tang, Zhenhua Li, Qingfu Zhang, Sam Kwong
Different from them, in this paper, we aim to link the generalization ability of a deep network to optimizing a new objective function.
no code implementations • 4 Nov 2018 • Xi Lin, Hui-Ling Zhen, Zhenhua Li, Qingfu Zhang, Sam Kwong
The proposed algorithm uses the Bayesian neural network as the scalable surrogate model.
no code implementations • 24 Oct 2018 • Zhengchao Zhang, Meng Li, Xi Lin, Yinhai Wang, Fang He
Multistep traffic forecasting on road networks is a crucial task in successful intelligent transportation system applications.