no code implementations • ICML 2020 • Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou
Besides the feature space evolving, it is noteworthy that the data distribution often changes in streaming data.
no code implementations • ICML 2020 • Lan-Zhe Guo, Zhen-Yu Zhang, Yuan Jiang, Yufeng Li, Zhi-Hua Zhou
Deep semi-supervised learning (SSL) has been shown very effectively.
no code implementations • 10 Feb 2024 • Zhen-Yu Zhang, Siwei Han, Huaxiu Yao, Gang Niu, Masashi Sugiyama
In this paper, motivated by Vapnik's principle, we propose a novel comparison-based CoT generation algorithm that directly identifies the most promising thoughts with the noisy feedback from the LLM.
no code implementations • 6 Jun 2022 • Zhen-Yu Zhang, Guo-Xiang Shao, Chun-Ming Qiu, Yue-Jie Hou, En-Ming Zhao, Chi-Chun Zhou
The results show that this method can achieve the early anomaly detection with the highest precision of 98. 21%, the recall rate 63. 58% and F1-score of 0. 774.
no code implementations • CVPR 2020 • Zhen-Yu Zhang, Stephane Lathuiliere, Elisa Ricci, Nicu Sebe, Yan Yan, Jian Yang
Online depth learning is the problem of consistently adapting a depth estimation model to handle a continuously changing environment.
no code implementations • 28 Mar 2020 • Hengzhu Tang, Yanan Cao, Zhen-Yu Zhang, Jiangxia Cao, Fang Fang, Shi Wang, Pengfei Yin
In this paper, we propose a Hierarchical Inference Network (HIN) to make full use of the abundant information from entity level, sentence level and document level.
Ranked #51 on Relation Extraction on DocRED
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Shiyao Cui, Bowen Yu, Tingwen Liu, Zhen-Yu Zhang, Xuebin Wang, Jinqiao Shi
Previous studies on the task have verified the effectiveness of integrating syntactic dependency into graph convolutional networks.
no code implementations • 23 Sep 2019 • Chunhui Guo, Zhicheng Fu, Zhen-Yu Zhang, Shangping Ren, Lui Sha
The framework allows computer scientists to work together with medical professionals to transform medical best practice guidelines into executable statechart models, Yakindu in particular, so that medical functionalities and properties can be quickly prototyped and validated.
1 code implementation • 10 Sep 2019 • Bowen Yu, Zhen-Yu Zhang, Xiaobo Shu, Yubin Wang, Tingwen Liu, Bin Wang, Sujian Li
Joint extraction of entities and relations aims to detect entity pairs along with their relations using a single model.
Ranked #1 on Relation Extraction on NYT-single
1 code implementation • IJCAI-19 2019 • Bowen Yu, Zhen-Yu Zhang, Tingwen Liu, Bin Wang, Sujian Li, Quangang Li
Relation extraction studies the issue of predicting semantic relations between pairs of entities in sentences.
Ranked #29 on Relation Extraction on TACRED
1 code implementation • 15 Jul 2019 • Zhen-Yu Zhang, Xiangfeng Luo, Tong Liu, Shaorong Xie, Jianshu Wang, Wei Wang, Yang Li, Yan Peng
Instability and slowness are two main problems in deep reinforcement learning.
no code implementations • CVPR 2019 • Zhen-Yu Zhang, Zhen Cui, Chunyan Xu, Yan Yan, Nicu Sebe, Jian Yang
In this paper, we propose a novel Pattern-Affinitive Propagation (PAP) framework to jointly predict depth, surface normal and semantic segmentation.
Ranked #51 on Semantic Segmentation on NYU Depth v2
1 code implementation • 29 May 2019 • Xiang Ji, Zhen-Yu Zhang, Andrew Holbrook, Akihiko Nishimura, Guy Baele, Andrew Rambaut, Philippe Lemey, Marc A. Suchard
To make this tractable, we present a linear-time algorithm for ${\cal O}\hspace{-0. 2em}\left( N \right)$-dimensional gradient evaluation and apply it to general continuous-time Markov processes of sequence substitution on a phylogenetic tree without a need to assume either stationarity or reversibility.
Computation Populations and Evolution Methodology
no code implementations • 17 Apr 2019 • Zhen-Yu Zhang, Stéphane Lathuilière, Andrea Pilzer, Nicu Sebe, Elisa Ricci, Jian Yang
Our proposal is evaluated on the wellestablished KITTI dataset, where we show that our online method is competitive withstate of the art algorithms trained in a batch setting.
no code implementations • 1 Feb 2019 • Zheng Fang, Yanan Cao, Dongjie Zhang, Qian Li, Zhen-Yu Zhang, Yanbing Liu
Entity linking is the task of aligning mentions to corresponding entities in a given knowledge base.
Ranked #6 on Entity Disambiguation on AIDA-CoNLL
no code implementations • 1 Jan 2019 • Long Zhang, Xuechao Sun, Yong Li, Zhen-Yu Zhang
Deep neural networks (DNNs) have been widely used in the fields such as natural language processing, computer vision and image recognition.
no code implementations • ECCV 2018 • Zhen-Yu Zhang, Zhen Cui, Chunyan Xu, Zequn Jie, Xiang Li, Jian Yang
In this paper, we propose a novel joint Task-Recursive Learning (TRL) framework for the closing-loop semantic segmentation and monocular depth estimation tasks.
Ranked #76 on Semantic Segmentation on NYU Depth v2
no code implementations • 7 Jul 2018 • Wenting Zhao, Chunyan Xu, Zhen Cui, Tong Zhang, Jiatao Jiang, Zhen-Yu Zhang, Jian Yang
In this paper, we aim to give a comprehensive analysis of when work matters by transforming different classical network structures to graph CNN, particularly in the basic graph recognition problem.
Ranked #3 on Graph Classification on IMDb-B