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mcKLR_mckNN
- This package includes two approaches to multi-class cost-sensitive learning, that is, mcKLR and mckNN. The descr iption of mcKLR can be found in our TPAMI paper and CVPR'08 paper; the descr iption of mckNN can be found in our TPAMI paper. Both approa
stprtool.rar
- 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines,
code
- 《多任务下的数据结构与算法》 光盘源代码- Multi-task under the data structure and algorithm, the source code CD-ROM
Data-Structures-and-Algorithms
- 多任务下的数据结构和算法这本书的全部源代码，用C实现的，包括基本的数据结构容器，引进了多任务。对从事软件开发与应用的工程技术人员具有较高的参考价值-Under multi-task data structure and algorithm of this book, all source code, using C to achieve, including the basic data structure of containers, the introduction of multi-tas
capi-0.21
- CAPI多核编程算法库0.21版，里面有分布式队列、分布式查找、分布式内存管理、任务图调度、动态任务调度等多种容器，新增了CWaitTaskScheduler任务调度容器和并行Strassen矩阵乘法等。-CAPI programming algorithm for multi-core library version 0.21, which are distributed queue, distributed search, distributed memory management, tas
2
- 实时有限多任务藻统设计与实现 这是我转的啊 看着觉得很好 很受启发 传上来 大家一起学习-Real-time multi-task with limited integration Design and Implementation of algae this is my turn, ah, a very enlightened look really good with everyone learn pass up
ourdev_249202
- 系统程序:多路信号实时采集和处理,并将处理后的数据以不同的 ** 方式显示.同时可根据按键输入实现任务调度. -System process: real-time multi-channel signal acquisition and processing, and post-processing data to be displayed** different. At the same time can be achieved according to key input
SPIDER_mclass
- Multi-class Coding (adapted from from LS-SVM for SPIDER). Encode (code_MOC, code_ECOC, code_OneVsAll, code_OneVsOns) and decode (codedist_hamming, codedist_bay) a multi-class classification task into multiple binary classifiers.
duorenwushujujiegou
- 多任务下的数据结构与算法，希望大家能够喜欢，多多交流-Under the multi-task data structure and algorithm, I hope you will like, more exchanges
Multitask-DSandAL
- 书和传统同类书籍的区别是除了介绍基本的数据结构容器如栈、队列、链表、树、二叉树、红黑树、AVL树和图之外，引进了多任务；还介绍了将任意数据结构容器变成支持多任务的方法-this Book and similar books is the difference between traditional Apart from the basic data structure container, such as stacks, queues, linked lists, trees, binary t
data-structures-and-algorithms
- 多任务下的数据结构和算法源码，包含了数据结构中链表、栈、队列和树等的知识，并详细讲解了这些算法在多线程下的应用，还提供了相关的测试程序-Multi-task data structure and algorithm source code, including data structures, linked lists, stacks, queues, and trees of knowledge, and explain in detail the application of these a
Multi-machine-scheduling
- 将对n个独立作业如何分配在m台相同的机器加工处理的多机调度问题进行解决，这就是我们要解决的任务。 本程序编写目的为使得解决多机调度问题的过程以图形界面方式动态的展示出来，以让用户能够轻易的看出解决的方案以及过程。采用java开发。 -Will be n independent jobs on m machines how to allocate the same machine processing of multi-machine scheduling problem to solv
MultitaskBCICode
- This the Multi task BCI Code including mt_gauss, mt_regression and test_err_linreg.-This is the Multi task BCI Code including mt_gauss, mt_regression and test_err_linreg.
CBBA
- 该CBBA(Consensus-Based Bundle Algorithm)算法可以解决带有任务属性、任务价值、任务时间窗等多种约束下的任务分配问题，结果以图形化展示，便于理解。-CBBA is a decentralized market-based protocol that provides provably good approximate solutions for multi-agent multi-task allocation problems over networks of
MALSAR1.1
- 多种多任务学习算法的工具箱 有代码有使用手册 matlab版-the toolbox of multi-task learning algorithms (matlab version)
MTWGP
- Multi-Task Warped Gaussian Process for Personalized Age Estimation 文章的matlab源代码-matlab code of paper Multi-Task Warped Gaussian Process for Personalized Age Estimation
MTBoost1
- Duchi and Singer [24] proposed a boosting method for multi-class classification problems by utilizing the structural sparsity of model parameters. They claimed that the method can be generalized for multi-task learning.
keras-master
- 最近一直在用keras，说点个人感受。 1、keras根植于python及theano，人气比较旺。 2、提供较为上层的框架，搞个深度学习的原型非常方便。 3、更新很快，我记得几个月前还没有multi-task的能力，最近再查就提供了graph的对象。 4、最重要的，文档很全。这点超过其它类似的基于theano的框架（Lasagne, Opendeep, Blocks）-Keras is a high-level neural networks library, written
matlab异步并行计算
- 基于matlab中parfeval函数和distributed分布式函数的多任务异步并行计算(Multi task asynchronous parallel computing based on parfeval function and distributed distributed function in MATLAB)
fast-rcnn-master
- Fast R-CNN是在R-CNN的基础上进行的改进，大致框架是一致的。总体而言，Fast R-CNN相对于R-CNN而言，主要提出了三个改进策略： 1. 提出了RoIPooling，避免了对提取的region proposals进行缩放到224x224，然后经过pre-trained CNN进行检测的步骤，加速了整个网络的learning与inference过程，这个是巨大的改进，并且RoIPooling是可导的，因此使得整个网络可以实现end-to-end learning，这个可以认为是