no code implementations • 4 Feb 2025 • Quan Zhang, Yuxin Qi, Xi Tang, Jinwei Fang, Xi Lin, Ke Zhang, Chun Yuan
There are two main challenges in applying SAM to image manipulation detection: a) reliance on manual prompts, and b) the difficulty of single-view information in supporting cross-dataset generalization.
2 code implementations • 19 Jan 2025 • WeiYu Chen, Xiaoyuan Zhang, Baijiong Lin, Xi Lin, Han Zhao, Qingfu Zhang, James T. Kwok
Multi-objective optimization (MOO) in deep learning aims to simultaneously optimize multiple conflicting objectives, a challenge frequently encountered in areas like multi-task learning and multi-criteria learning.
no code implementations • 19 Jan 2025 • Quan Zhang, Yuxin Qi, Xi Tang, Rui Yuan, Xi Lin, Ke Zhang, Chun Yuan
Pseudo-label learning methods have been widely applied in weakly-supervised temporal action localization.
no code implementations • 13 Jan 2025 • Ping Guo, Cheng Gong, Xi Lin, Fei Liu, Zhichao Lu, Qingfu Zhang, Zhenkun Wang
Crafting adversarial examples is crucial for evaluating and enhancing the robustness of Deep Neural Networks (DNNs), presenting a challenge equivalent to maximizing a non-differentiable 0-1 loss function.
1 code implementation • 25 Dec 2024 • Ping Guo, Qingfu Zhang, Xi Lin
We propose a novel framework that utilizes LLMs in an evolutionary search methodology, augmented by a dynamic knowledge library that integrates and refines insights in an \textit{open-ended manner}.
1 code implementation • 23 Dec 2024 • Fei Liu, Rui Zhang, Zhuoliang Xie, Rui Sun, Kai Li, Xi Lin, Zhenkun Wang, Zhichao Lu, Qingfu Zhang
We introduce LLM4AD, a unified Python platform for algorithm design (AD) with large language models (LLMs).
1 code implementation • 10 Dec 2024 • Ke Xue, Ruo-Tong Chen, Xi Lin, Yunqi Shi, Shixiong Kai, Siyuan Xu, Chao Qian
In modern chip design, placement aims at placing millions of circuit modules, which is an essential step that significantly influences power, performance, and area (PPA) metrics.
no code implementations • 14 Nov 2024 • Xi Lin, Shixuan Zhao, Xinxu Wei, Amir Shmuel, YongJie Li
In the knowledge distillation stage, the codebook facilitates the transfer of rich knowledge from a heterogeneous teacher model to a student model, while the semi-supervised approach further enhances the student model's exposure to diverse learning samples.
no code implementations • 11 Oct 2024 • Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Zhe Zhao, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhichao Lu, Zhenkun Wang, Qingfu Zhang
Algorithm Design (AD) is crucial for effective problem-solving across various domains.
no code implementations • 25 Sep 2024 • Shunyu Yao, Fei Liu, Xi Lin, Zhichao Lu, Zhenkun Wang, Qingfu Zhang
We propose the first LLM-based multi-objective heuristic search framework, Multi-objective Evolution of Heuristic (MEoH), which integrates LLMs in a zero-shot manner to generate a non-dominated set of heuristics to meet multiple design criteria.
no code implementations • 17 Sep 2024 • Xinxu Wei, Xi Lin, Haiyun Liu, Shixuan Zhao, YongJie Li
Effective retinal vessel segmentation requires a sophisticated integration of global contextual awareness and local vessel continuity.
1 code implementation • 4 Sep 2024 • Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Yifan Chen, Han Zhao, Qingfu Zhang
Multiobjective optimization problems (MOPs) are prevalent in machine learning, with applications in multi-task learning, learning under fairness or robustness constraints, etc.
no code implementations • 24 Aug 2024 • Wenhao Li, Yichao Cao, Xiu Su, Xi Lin, Shan You, Mingkai Zheng, Yi Chen, Chang Xu
It can generate high-quality videos with chain of off-the-shelf diffusion model experts, each expert responsible for a decoupled subtask.
no code implementations • 19 Aug 2024 • Daniel Cunha Oliveira, Yutong Lu, Xi Lin, Mihai Cucuringu, Andre Fujita
To the best of our knowledge, this is the first study to conduct a comprehensive comparative analysis among state-of-the-art causal discovery algorithms, benchmarked against non-causal feature selection techniques, in the application of forecasting asset returns.
no code implementations • 15 Jul 2024 • Rui Zhang, Fei Liu, Xi Lin, Zhenkun Wang, Zhichao Lu, Qingfu Zhang
Automated heuristic design (AHD) has gained considerable attention for its potential to automate the development of effective heuristics.
no code implementations • 22 Jun 2024 • Siyuan Li, Xi Lin, Yaju Liu, Gaolei Li, Jianhua Li
Furthermore, we assess the performance of OpticGAI on two NP-hard optical network problems, Routing and Wavelength Assignment (RWA) and dynamic Routing, Modulation, and Spectrum Allocation (RMSA), to show the feasibility of the AI-generated policy paradigm.
no code implementations • 30 May 2024 • Xi Lin, Yilu Liu, Xiaoyuan Zhang, Fei Liu, Zhenkun Wang, Qingfu Zhang
Existing optimization methods often focus on finding a set of Pareto solutions with different optimal trade-offs among the objectives.
1 code implementation • 20 May 2024 • Fei Liu, Xi Lin, Weiduo Liao, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan
To be concrete, we propose a novel prompt learning method to facilitate fast zero-shot adaptation of a pre-trained model to solve routing problem instances from different distributions.
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.
1 code implementation • 23 Apr 2024 • Sunan He, Yuxiang Nie, Hongmei Wang, Shu Yang, Yihui Wang, Zhiyuan Cai, Zhixuan Chen, Yingxue Xu, Luyang Luo, Huiling Xiang, Xi Lin, Mingxiang Wu, Yifan Peng, George Shih, Ziyang Xu, Xian Wu, Qiong Wang, Ronald Cheong Kin Chan, Varut Vardhanabhuti, Winnie Chiu Wing Chu, Yefeng Zheng, Pranav Rajpurkar, Kang Zhang, Hao Chen
Specifically, we propose a cooperative framework, Generalist-Specialist Collaboration (GSCo), which consists of two stages, namely the construction of GFM and specialists, and collaborative inference on downstream tasks.
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.
1 code implementation • 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, 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.
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
+2
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.
4 code implementations • 4 Jan 2024 • Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang
EoH represents the ideas of heuristics in natural language, termed thoughts.
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.
1 code implementation • 26 Sep 2023 • Vik Shirvaikar, Xi Lin, Chris Holmes
The estimation of heterogeneous treatment effects (HTE) across different subgroups in a population is of significant interest in clinical trial analysis.
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 • 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 • 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 • 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.