针对Top-k高效用项集挖掘算法在挖掘过程中忽略内存管理的问题,提出基于DBP的Top-k高效用项集挖掘算法TKBPH(Top-k buffer pool high utility itemsets mining),采用数据缓冲池(DBP)结构存储效用链表,并由索引链表记录效用链表在DBP的位置.数据缓冲池根据挖掘过程情况在数据缓冲池尾部动态插入和删除效用链表,通过索引链表...
The novel disseminated framework for pooled location based information inception and sharing, considering the development in internet application and location access in mobile devices. It allows the versatile clients to impart their involvement with a wide range of points of interests (POI). The ...
面试高频问题之 Top K | 小旭讲解 基础算法系列 第 K 大的数 堆 - EP7 1920播放 Java面试必知必会.Java基础.05.动态代理(JDK/CGLIB) 4.8万播放 并发编程 | 低频的业务场景可以通过corePoolSize == 0来节省系统资源吗? 1220播放 彻底拿捏Spring循环依赖以及三个级别缓存 2924播放 黑马程序员SSM框架教程_Spring...
面试高频问题之 Top K | 小旭讲解 基础算法系列 第 K 大的数 堆 - EP7 1920播放 Java面试必知必会.Java基础.05.动态代理(JDK/CGLIB) 4.8万播放 并发编程 | 低频的业务场景可以通过corePoolSize == 0来节省系统资源吗? 1220播放 彻底拿捏Spring循环依赖以及三个级别缓存 2924播放 黑马程序员SSM框架教程_Spring...
tf.nn.max_pool tf.nn.max_pool 参数说明 value:输入值,一个四维tensor,形状为[batch, height, width, channels] ksize:一个int或者list,长度为1,2或者4. 代表在每一个维度上的池化窗口的大小,一般设置为[1, height, width, 1],因为通常在batch和channel上池化没有意义 strides:一个int或者list,长度为...
() for pool in self.pools: pool.reset_parameters() self.lin1.reset_parameters() self.lin2.reset_parameters() def forward(self, data): x, edge_index, batch = data.x, data.edge_index, data.batch x = F.relu(self.conv1(x, edge_index)) xs = [global_mean_pool(x, batch)] for ...
This link says that earlier versions of Tomcat (before 7.0.54) "renews its threads" thru ThreadPoolExecutor.run(). Why doesn't the init() method of contained Servlets seem to get called agai...Excel 12.0 Interop acting randomly on Excel 2016 using C# I have written C# application using...
Constraint-based data mining [24] has been widely used for finding frequent items or patterns in a given pool of data [17,18]. Various types of constraints can be used in mining, such as knowledge type constraints, data constraints, dimension constraints, interestingness constraints, rule constra...
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pool3 13x13x192 7x7x192 最大池化层 dropout3 7x7x192 7x7x192 spatial dropout dense1 7x7x192 256 采用ReLU激活、带L2正则化、含BN与dropout的全连接层 softmax_linear 256 65 softmax分类器 上表中所列举的conv_stack, inception v2 module均在layers.py中实现。其中inception v2 module具体结构如下...