Search Results for author: Zhen-Yu Zhang

Found 18 papers, 5 papers with code

Learning with Feature and Distribution Evolvable Streams

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.

Generating Chain-of-Thoughts with a Direct Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought

no code implementations10 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.

Language Modelling Large Language Model

Early Abnormal Detection of Sewage Pipe Network: Bagging of Various Abnormal Detection Algorithms

no code implementations6 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.

Anomaly Detection

Online Depth Learning Against Forgetting in Monocular Videos

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.

Depth Estimation Meta-Learning

HIN: Hierarchical Inference Network for Document-Level Relation Extraction

no code implementations28 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.

Document-level Relation Extraction Relation +2

Formalism for Supporting the Development of Verifiably Safe Medical Guidelines with Statecharts

no code implementations23 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.

Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy

1 code implementation10 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.

Relation Extraction

Gradients do grow on trees: a linear-time ${\cal O}\hspace{-0.2em}\left( N \right)$-dimensional gradient for statistical phylogenetics

1 code implementation29 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

Online Adaptation through Meta-Learning for Stereo Depth Estimation

no code implementations17 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.

Meta-Learning Stereo Depth Estimation

A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks

no code implementations1 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.


Joint Task-Recursive Learning for Semantic Segmentation and Depth Estimation

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.

Monocular Depth Estimation Segmentation +1

When Work Matters: Transforming Classical Network Structures to Graph CNN

no code implementations7 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.

Graph Classification Video Understanding

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