Searchpruningreturned 19 results

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1

Data pruning method based on consistency committee of small-scale heterogeneous language models

基于小规模异构语言模型一致性委员会的数据剪枝方法

Wang Kaiwen

Wang Yunzhe

Tan Wei

Fu Qiming

Lu You

Chen Jianping

large language model

data pruning

multi-model committee

perplexity

Accepted Paper No. 12, 2025 : doi:10.19734/j.issn.1001-3695.2025.05.0139

2

Incremental mining method of spatial co-location patterns based on changed participating instances

基于变化参与实例的空间并置模式增量挖掘方法

Lu Junli

Chang Xin

Luo Haoyu

Liu Shihu

spatial co-location pattern

incremental mining

changed participation instance

instance search space

pattern pruning technique

No. 2, 2025 : 431-440 doi:10.19734/j.issn.1001-3695.2024.07.0277

3

Directional fuzzing based on multi-objective domination analysis and path dynamic pruning optimization

基于多目标支配分析和路径动态修剪优化的定向模糊测试技术

Li Zeyuan

Yin Zhongxu

Zong Guoxiao

Sang Haiya

directed fuzzing

vulnerability mining

multi-objective orientation

program analysis

No. 11, 2024 : 3455-3463 doi:10.19734/j.issn.1001-3695.2024.01.0060

4

Interpretability enhancement model of random forest using ensemble pruning and multi-objective evolutionary algorithm

利用集成剪枝和多目标优化算法的随机森林可解释增强模型

Li Yang

Liao Mengjie

Zhang Jian

random forest

interpretability enhancement

ensemble pruning

rule extraction

multi-objective evolutionary algorithm

No. 10, 2024 : 2947-2954 doi:10.19734/j.issn.1001-3695.2024.02.0047

5

Face image inpainting algorithm based on edge prior fusion dynamic gating features

基于边缘先验融合动态门控特征的人脸图像修复

Chen Ting

Wang Tong

Zhang Jiwu

Chen Guangchen

face image inpainting

dynamic gated convolution

U-shaped encoded texture inpainting network

U-shaped pruning network

No. 11, 2023 : 3478-3484 doi:10.19734/j.issn.1001-3695.2023.03.0123

6

Relationship-oriented entity relationship extraction method combining dependent information

融合依存信息的关系导向型实体关系抽取方法

Wang Jinghui

Lu Ling

Duan Zhili

Zhang Liang

Wang Yuke

entity relationship extraction

dependency syntactic parsing

pruning

relationship orientation

synonym

No. 5, 2023 : 1410-1415,1440 doi:10.19734/j.issn.1001-3695.2022.10.0540

7

Obstacle avoidance path planning of manipulator based on PS-RRT algorithm

基于PS-RRT算法的机械臂避障路径规划

Wang Hongli

Xiang Guofei

Zhu Yuqi

Dian Songyi

manipulator

path planning

rapidly exploring random trees

partition dynamic sampling

node rejection

path pruning

No. 1, 2023 : 42-46 doi:10.19734/j.issn.1001-3695.2022.06.0287

8

User-sensitive top-k dominating query method based on upper bound pruning

一种基于上界值剪枝的用户敏感top-k dominating查询方法

Xu Chao

Wu Danqi

Chen Yong

Lei Jintao

incomplete data

top-k dominating query

user sensitivity

weight dominance grade

upper bound value pruning

No. 1, 2023 : 198-203,208 doi:10.19734/j.issn.1001-3695.2022.04.0232

9

Adaptive threshold-based recurrent pruning algorithm

基于自适应阈值的循环剪枝算法

Wang Yizhong

Guo Zhendong

Fang Chen

Yang Guowei

Wang Qiqi

Guo Xiaoyong

deep learning

convolutional neural network

adaptive pruning threshold

channel pruning

layer pruning

No. 5, 2022 : 1467-1471,1477 doi:10.19734/j.issn.1001-3695.2021.09.0413

10

Research on FPGM pruning based on sensitivity analysis

基于灵敏度分析的FPGM剪枝算法研究

Ran Guangjin

Li Zhen

Li Liangrong

deep learning

network pruning

image classification

sensitivity

No. 1, 2022 : 141-145 doi:10.19734/j.issn.1001-3695.2021.06.0246

11

Improved parallel association rules incremental mining algorithm

改进的并行关联规则增量挖掘算法

Mao Yimin

Deng Qianhu

Deng Xiaohong

Liu Wei

Can-tree

rough set

merge pruning

big data

incremental mining

No. 10, 2021 : 2974-2980 doi:10.19734/j.issn.1001-3695.2021.03.0084

12

Knowledge distillation method for remote sensing satellite image classification based on pruning network

基于剪枝网络的知识蒸馏对遥感卫星图像分类方法

Yang Hongbing

Chi Yongxin

Wang Jinguang

remote sensing image

deep learning

attention mechanism

model pruning

knowledge of distillation

No. 8, 2021 : 2469-2473 doi:10.19734/j.issn.1001-3695.2020.07.0387

13

Target detection algorithm in industrial scene based on SlimYOLOv3

基于SlimYOLOv3的工业场景目标检测算法

Liu Xinrou

Li Yang

Song Wenjun

machine vision

intelligent industry

target detection

model pruning

YOLOv3

No. 6, 2021 : 1889-1893 doi:10.19734/j.issn.1001-3695.2020.06.0203

14

Parallel deep convolution neural network optimization algorithm based on big data

基于大数据的并行化深度卷积神经网络优化算法

Mao Yimin

Zhang Ruipeng

Cao Wenliang

deep convolutional neural network(DCNN) algorithm

MapReduce framework

conjugate gradient strategy based on modified secant equation(CGMSE)

pruning method based on feature map(PFM) strategy

load balancing strategy based balancing load rate(LBRLA) strategy

No. 5, 2021 : 1416-1421 doi:10.19734/j.issn.1001-3695.2020.04.0112

15

Neural network hybrid compression method based on information bottleneck

一种基于信息瓶颈的神经网络混合压缩方法

Zhuo Yue

Jiang Li

information bottleneck

pruning

ternary quantization

model compression

No. 5, 2021 : 1463-1467 doi:10.19734/j.issn.1001-3695.2020.01.0009

16

Algorithm research of solving multiprocessor scheduling problem based on pruning algorithm

基于剪枝算法解决多处理机调度问题的算法研究

Li Bo

Zhang Xiao

Yan Jingyi

multiprocessor scheduling problem

pruning algorithm

fool algorithm

greedy algorithm

genetic algorithm

differential evolution algorithm

No. 8, 2020 : 2386-2389 doi:10.19734/j.issn.1001-3695.2019.02.0064

17

Method of pruning decision tree model and block-wise to speed-up ranking candidate documents

加快排序文档的剪枝决策树和分块方法

Li Weijiang

Chang Wei

Yu Zhengtao

learning to rank

cache

efficiency

pruning

No. 1, 2020 : 193-197 doi:10.19734/j.issn.1001-3695.2018.05.0443

18

Parallel K-means algorithm with differential privacy preservation and outlier pruning

支持差分隐私保护及离群点消除的并行K-means算法

Fan Yikang

Liu Jianwei

K-means clustering

outlier pruning(DP)

differential privacy(DP)

MapReduce

No. 6, 2019 : 1776-1781,1787 doi:10.19734/j.issn.1001-3695.2017.12.0825

19

Maximal frequent itemset mining algorithm based on B-list

基于B-list的最大频繁项集挖掘算法

Zhang Chang

Wen Kai

Zheng Yunjun

maximal frequent itemsets mining

depth-first search

pruning techniques

superset detection

No. 2, 2019 : 351-354 doi:10.19734/j.issn.1001-3695.2017.08.0873