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杂记

在瑞典做硕士论文 (一)

在瑞典做硕士论文 (一) 导言 在Uppsala University 学习的第二年做硕士论文(Thesis)是大多数国际学生的选择。我从2020年10月开始找愿意接收我做Thesis的工业界机构,于当年12月中旬确定在Ericsson做Thesis student and Researcher. 大多数的国际硕士生都会选择在最后两个Periods做Thesis, 以期望能够在做Thesis的公司更容易地找到职位或者在教授那里拿到PhD的 offfer. November 19, 2020 15:40 Uppsal…

2021年8月13日 0条评论 8501点热度 3人点赞 Dong Wang 阅读全文
深度学习

Natural Computation Methods for Machine Learning Note 15

Natural Computation Methods for Machine Learning Note 15 In this article, we talk about Particle Swarm Optimization. In last post, we talked Computational tools, including Cellular automata Ant Colony Optimization Particle Swarm Optimization Particle Swarm Opt…

2020年3月28日 0条评论 5207点热度 1人点赞 Dong Wang 阅读全文
深度学习

Natural Computation Methods for Machine Learning Note 14

Natural Computation Methods for Machine Learning Note 14 Swarm Intelligence Intelligence <- Social behavior Intelligence can emerge from social interaction. Emergent behaviour – when a group behaves in ways that were not ”programmed” into its members Swarm …

2020年3月25日 0条评论 5439点热度 0人点赞 Dong Wang 阅读全文
深度学习

Natural Computation Methods for Machine Learning Note 13

Natural Computation Methods for Machine Learning Note 13 Properties of EC EC is parallel search (many balls in the landscape). Want to prevent all individuals from converging to the same solution (premature convergence – a common problem) The task of mutation …

2020年3月20日 0条评论 4320点热度 0人点赞 Dong Wang 阅读全文
深度学习

Natural Computation Methods for Machine Learning Note 12

Natural Computation Methods for Machine Learning Note 12 From course, I learned Evolutional Computing. Evolutionary computing (EC) population method Used for problems where the task is to maximize some measure of success Same family of problems as in RL, but v…

2020年3月20日 0条评论 4044点热度 0人点赞 Dong Wang 阅读全文
深度学习

Natural Computation Methods for Machine Learning Note 11

Natural Computation Methods for Machine Learning Note 11 Let us firstly revisit completive learning and SOFM Review CL and SOFM A node position (in the input space) is its weight vector, i.e. nodes move around in the same space as the data. Purpose of unsuperv…

2020年3月4日 0条评论 4536点热度 0人点赞 Dong Wang 阅读全文
深度学习

Natural Computation Methods for Machine Learning Note 10

Natural Computation Methods for Machine Learning Note 10 In this note, we are going talk about Deep Learning very briefly. Radial Basis Function Networks RBFNs are feedforward networks, where: The hidden nodes (the RBF nodes) compute distances, instead of weig…

2020年3月2日 0条评论 4635点热度 0人点赞 Dong Wang 阅读全文
深度学习

Natural Computation Methods for Machine Learning Note 09

Unsupervised Learning To learn from unlabeled data (only inputs, no target information). Most often for classification. Requires that class membership can be detected by structural properties (features) in the data, and that the learning system can be fund the…

2020年3月2日 0条评论 4227点热度 1人点赞 Dong Wang 阅读全文
深度学习

Natural Computation Methods for Machine Learning Note 08

Natural Computation Methods for Machine Learning Note 08 ex) Tic-Tac-Toe Assign value to each board position (state): +1 if the state is a winning terminal state. 0 if the state is a losing terminal state +0.5 to all other states (terminal and non–terminal) pl…

2020年2月20日 0条评论 5045点热度 0人点赞 Dong Wang 阅读全文
深度学习

Natural Computation Methods for Machine Learning Note 07

Natural Computation Methods for Machine Learning Note 07 From today, we are going to introduce reinforcement learning(RL). Forget ANNs for a while - RL is a field in its own right, independent from ANNs. However, as we will see, ANNs are sometimes used in RL. …

2020年2月14日 0条评论 4607点热度 0人点赞 Dong Wang 阅读全文
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Dong Wang

I am a PhD student of TU Graz in Austria. My research interests include Embedded/Edge AI, efficient machine learning, model sparsity, deep learning, computer vision, and IoT. I would like to understand the foundational problems in deep learning.

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