no code implementations • 8 May 2024 • Sha Wang, Yuchen Li, Hanhua Xiao, Zhifeng Bao, Lambert Deng, Yanfei Dong
Efficient news exploration is crucial in real-world applications, particularly within the financial sector, where numerous control and risk assessment tasks rely on the analysis of public news reports.
no code implementations • 5 May 2024 • Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu
Our focus is on understanding when inexact RGD converges and what is the complexity in the general nonconvex and constrained setting.
no code implementations • 1 Apr 2024 • Zhonghao Lyu, Yuchen Li, Guangxu Zhu, Jie Xu, H. Vincent Poor, Shuguang Cui
Based on our analytical results, we then propose a joint communication and computation resource management design to minimize an average squared gradient norm bound, subject to constraints on the transmit power, overall system energy consumption, and training delay.
no code implementations • 9 Jan 2024 • Haoyi Xiong, Xuhong LI, Xiaofei Zhang, Jiamin Chen, Xinhao Sun, Yuchen Li, Zeyi Sun, Mengnan Du
Given the complexity and lack of transparency in deep neural networks (DNNs), extensive efforts have been made to make these systems more interpretable or explain their behaviors in accessible terms.
no code implementations • 16 Dec 2023 • Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu
Block majorization-minimization (BMM) is a simple iterative algorithm for nonconvex optimization that sequentially minimizes a majorizing surrogate of the objective function in each block coordinate while the other block coordinates are held fixed.
no code implementations • NeurIPS 2023 • Kaiyue Wen, Yuchen Li, Bingbin Liu, Andrej Risteski
Interpretability methods aim to understand the algorithm implemented by a trained model (e. g., a Transofmer) by examining various aspects of the model, such as the weight matrices or the attention patterns.
no code implementations • 20 Nov 2023 • Sha Wang, Yuchen Li, Hanhua Xiao, Lambert Deng, Yanfei Dong
The creation of news timeline is essential for a comprehensive and contextual understanding of events as they unfold over time.
1 code implementation • 27 Oct 2023 • Habib Slim, Xiang Li, Yuchen Li, Mahmoud Ahmed, Mohamed Ayman, Ujjwal Upadhyay, Ahmed Abdelreheem, Arpit Prajapati, Suhail Pothigara, Peter Wonka, Mohamed Elhoseiny
In this work, we present 3DCoMPaT$^{++}$, a multimodal 2D/3D dataset with 160 million rendered views of more than 10 million stylized 3D shapes carefully annotated at the part-instance level, alongside matching RGB point clouds, 3D textured meshes, depth maps, and segmentation masks.
no code implementations • 3 Oct 2023 • Hongyi Duan, Qingyang Li, Yuchen Li, Jianan Zhang, Yuming Xie
As global attention on renewable and clean energy grows, the research and implementation of microgrids become paramount.
no code implementations • 3 Oct 2023 • Qingyang Li, Yuchen Li, Hongyi Duan, JiaLiang Kang, Jianan Zhang, Xueqian Gan, Ruotong Xu
In this paper, the limitations of YOLOv5s model on small target detection task are deeply studied and improved.
no code implementations • 14 Aug 2023 • Siyu Teng, Luxi Li, Yuchen Li, Xuemin Hu, Lingxi Li, Yunfeng Ai, Long Chen
Firstly, we propose a multi-task motion planning algorithm, called FusionPlanner, for autonomous mining trucks by the multi-sensor fusion method to adapt both lateral and longitudinal control tasks for unmanned transportation.
no code implementations • 3 Jun 2023 • Long Chen, Siyu Teng, Bai Li, Xiaoxiang Na, Yuchen Li, Zixuan Li, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang
Growing interest in autonomous driving (AD) and intelligent vehicles (IVs) is fueled by their promise for enhanced safety, efficiency, and economic benefits.
no code implementations • 12 May 2023 • Long Chen, Yuchen Li, Chao Huang, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang
Our work is divided into 3 independent articles and the first part is a Survey of Surveys (SoS) for total technologies of AD and IVs that involves the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions.
no code implementations • 30 Mar 2023 • Long Chen, Yuchen Li, Chao Huang, Bai Li, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Xiaoxiang Na, Zixuan Li, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits.
no code implementations • 17 Mar 2023 • Siyu Teng, Xuemin Hu, Peng Deng, Bai Li, Yuchen Li, Dongsheng Yang, Yunfeng Ai, Lingxi Li, Zhe XuanYuan, Fenghua Zhu, Long Chen
Intelligent vehicles (IVs) have gained worldwide attention due to their increased convenience, safety advantages, and potential commercial value.
1 code implementation • 7 Mar 2023 • Yuchen Li, Yuanzhi Li, Andrej Risteski
While the successes of transformers across many domains are indisputable, accurate understanding of the learning mechanics is still largely lacking.
no code implementations • 13 Dec 2022 • Zizhang Wu, Man Wang, Weiwei Sun, Yuchen Li, Tianhao Xu, Fan Wang, Keke Huang
Channel and spatial attention mechanism has proven to provide an evident performance boost of deep convolution neural networks (CNNs).
no code implementations • 22 Nov 2022 • Yuchen Li, Zongxia Liang, Shunzhi Pang
We study the continuous-time portfolio selection under monotone mean-variance (MMV) preferences in a jump-diffusion model and give an explicit solution different from that under classical mean-variance (MV) preferences for the first time.
1 code implementation • 2 Nov 2022 • Yanhao Wang, Yuchen Li, Francesco Bonchi, Ying Wang
Submodular function maximization is a fundamental combinatorial optimization problem with plenty of applications -- including data summarization, influence maximization, and recommendation.
1 code implementation • 21 Oct 2022 • Bowen Zhao, Jiuding Sun, Bin Xu, Xingyu Lu, Yuchen Li, Jifan Yu, Minghui Liu, Tingjian Zhang, Qiuyang Chen, Hanming Li, Lei Hou, Juanzi Li
To tackle these issues, we propose EDUKG, a heterogeneous sustainable K-12 Educational Knowledge Graph.
no code implementations • 12 Aug 2022 • Haimiao Mo, Yuchen Li, Shanlin Yang, Wei zhang, Shuai Ding
To address these issues, we propose a framework with spatiotemporal feature fusion for detecting anxiety nonintrusively.
3 code implementations • 9 Jun 2022 • Guocheng Qian, Yuchen Li, Houwen Peng, Jinjie Mai, Hasan Abed Al Kader Hammoud, Mohamed Elhoseiny, Bernard Ghanem
In this work, we revisit the classical PointNet++ through a systematic study of model training and scaling strategies, and offer two major contributions.
Ranked #3 on 3D Semantic Segmentation on OpenTrench3D
1 code implementation • 29 Mar 2022 • Ashwini Pokle, Jinjin Tian, Yuchen Li, Andrej Risteski
Some recent works however have shown promising results for non-contrastive learning, which does not require negative samples.
no code implementations • 9 Feb 2022 • Yuchen Li, Frank Rudzicz
We scale perceived distances of the core-set algorithm by a factor of uncertainty and search for low-confidence configurations, finding significant improvements in sample efficiency across CIFAR10/100 and SVHN image classification, especially in larger acquisition sizes.
no code implementations • CVPR 2022 • Yuchen Li, Zixuan Li, Siyu Teng, Yu Zhang, YuHang Zhou, Yuchang Zhu, Dongpu Cao, Bin Tian, Yunfeng Ai, Zhe XuanYuan, Long Chen
The main contributions of the AutoMine dataset are as follows: 1. The first autonomous driving dataset for perception and localization in mine scenarios.
no code implementations • 24 Jun 2021 • Yuchen Li, Yifan Bao, Liyao Xiang, Junhan Liu, Cen Chen, Li Wang, Xinbing Wang
Federated learning is emerging as a machine learning technique that trains a model across multiple decentralized parties.
no code implementations • ACL 2021 • Yuchen Li, Andrej Risteski
Concretely, we ground this question in the sandbox of probabilistic context-free-grammars (PCFGs), and identify a key aspect of the representational power of these approaches: the amount and directionality of context that the predictor has access to when forced to make parsing decision.
1 code implementation • 7 Dec 2020 • Hanbaek Lyu, Yuchen Li
Block majorization-minimization (BMM) is a simple iterative algorithm for nonconvex constrained optimization that sequentially minimizes majorizing surrogates of the objective function in each block coordinate while the other coordinates are held fixed.
1 code implementation • 28 Jul 2020 • Jingjing Wang, Yanhao Wang, Wenjun Jiang, Yuchen Li, Kian-Lee Tan
We first propose a generic edge sampling (ES) algorithm for estimating the number of instances of any temporal motif.
no code implementations • 19 Jul 2020 • Yanhao Wang, Michael Mathioudakis, Yuchen Li, Kian-Lee Tan
Extracting a small subset of representative tuples from a large database is an important task in multi-criteria decision making.
Data Structures and Algorithms Databases
1 code implementation • 29 May 2020 • Yanhao Wang, Yuchen Li, Raymond Chi-Wing Wong, Kian-Lee Tan
Selecting a small set of representatives from a large database is important in many applications such as multi-criteria decision making, web search, and recommendation.
Databases Data Structures and Algorithms
1 code implementation • 4 Sep 2019 • Yu Shi, Jiaming Shen, Yuchen Li, Naijing Zhang, Xinwei He, Zhengzhi Lou, Qi Zhu, Matthew Walker, Myunghwan Kim, Jiawei Han
Extensive experiments on two large real-world datasets demonstrate the effectiveness of HyperMine and the utility of modeling context granularity.
2 code implementations • 24 Jun 2019 • Yuchen Li, Frank Rudzicz, Jekaterina Novikova
We seek to improve the data efficiency of neural networks and present novel implementations of parameterized piece-wise polynomial activation functions.
1 code implementation • 9 May 2019 • Yanhao Wang, Yuchen Li, Kian-Lee Tan
This paper investigates the problem of maintaining a coreset to preserve the minimum enclosing ball (MEB) for a sliding window of points that are continuously updated in a data stream.
1 code implementation • 6 Mar 2019 • Ahmed Ayyad, Yuchen Li, Nassir Navab, Shadi Albarqouni, Mohamed Elhoseiny
We develop a random walk semi-supervised loss that enables the network to learn representations that are compact and well-separated.
no code implementations • 23 Jan 2019 • Hongyu Gong, Yuchen Li, Suma Bhat, Pramod Viswanath
Misspelled words of the malicious kind work by changing specific keywords and are intended to thwart existing automated applications for cyber-environment control such as harassing content detection on the Internet and email spam detection.
1 code implementation • ICLR 2019 • Safwan Hossain, Kiarash Jamali, Yuchen Li, Frank Rudzicz
Current approaches attempt to learn the transformation from a noise sample to a generated data sample in one shot.
2 code implementations • 18 Nov 2018 • Yuchen Li, Safwan Hossain, Kiarash Jamali, Frank Rudzicz
We consider a classifier whose test set is exposed to various perturbations that are not present in the training set.
1 code implementation • 15 Jun 2017 • Yanhao Wang, Yuchen Li, Kian-Lee Tan
By keeping much fewer checkpoints, KW$^{+}$ achieves higher efficiency than KW while still guaranteeing a $\frac{1-\varepsilon'}{2+2d}$-approximate solution for SMDK.
no code implementations • 6 Feb 2017 • Yanhao Wang, Qi Fan, Yuchen Li, Kian-Lee Tan
Influence maximization (IM), which selects a set of $k$ users (called seeds) to maximize the influence spread over a social network, is a fundamental problem in a wide range of applications such as viral marketing and network monitoring.
Social and Information Networks Data Structures and Algorithms