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<?xml version="1.0" encoding="utf-8"?>
<feed xmlns="http://www.w3.org/2005/Atom">
<title>YuleZhang's Blog</title>
<subtitle>坚持走自己的路！</subtitle>
<link href="/atom.xml" rel="self"/>
<link href="http://www.yulezhang.com/"/>
<updated>2024-03-14T15:08:36.765Z</updated>
<id>http://www.yulezhang.com/</id>
<generator uri="https://hexo.io/">Hexo</generator>
<entry>
<title>Web技术梳理</title>
<link href="http://www.yulezhang.com/2024/03/14/72Web-summary/"/>
<id>http://www.yulezhang.com/2024/03/14/72Web-summary/</id>
<published>2024-03-14T14:47:40.000Z</published>
<updated>2024-03-14T15:08:36.765Z</updated>
<summary type="html">
<p><img src="/images/web.jpg" alt="cover"></p>
<p>经常迷惑于各种前端技术，有了js/html/css三件套，但又有React/Angualar/Vue等各种技术，新技术框架层出不穷，搞得人晕头转向，今天咱们就来捋一捋。</p>
</summary>
<category term="前端" scheme="http://www.yulezhang.com/categories/%E5%89%8D%E7%AB%AF/"/>
</entry>
<entry>
<title>Chatgpt使用及账号出售</title>
<link href="http://www.yulezhang.com/2023/04/28/71ChatgptAccount/"/>
<id>http://www.yulezhang.com/2023/04/28/71ChatgptAccount/</id>
<published>2023-04-28T05:27:40.000Z</published>
<updated>2024-03-14T15:09:19.044Z</updated>
<summary type="html">
<p><img src="/images/openai.jpg" alt="cover"></p>
<h2 id="chatgpt使用体验">Chatgpt使用体验</h2>
<p>自打用chatgpt已经两三个月了，作为追热点的一员，能明显感觉到它的<strong>社区、生态、相关研究</strong>正在迅速铺开。</p>
</summary>
</entry>
<entry>
<title>2023秋招总结</title>
<link href="http://www.yulezhang.com/2023/03/14/70CampusRecruitment/"/>
<id>http://www.yulezhang.com/2023/03/14/70CampusRecruitment/</id>
<published>2023-03-14T13:39:40.000Z</published>
<updated>2024-03-14T15:09:56.602Z</updated>
<summary type="html">
<h3 id="秋招">秋招</h3>
<p>秋招可选岗位</p>
<p><img src="/assets/image-20230314211200522.png" alt="image-20230314211200522"></p>
</summary>
<category term="实习" scheme="http://www.yulezhang.com/categories/%E5%AE%9E%E4%B9%A0/"/>
<category term="随笔" scheme="http://www.yulezhang.com/tags/%E9%9A%8F%E7%AC%94/"/>
</entry>
<entry>
<title>力扣1044-Longest Duplicate Substring C++</title>
<link href="http://www.yulezhang.com/2021/10/01/70leetcode-1044/"/>
<id>http://www.yulezhang.com/2021/10/01/70leetcode-1044/</id>
<published>2021-10-01T08:15:00.000Z</published>
<updated>2024-03-14T15:08:46.582Z</updated>
<summary type="html">
<p><img src="/assets/1635668255065.png" alt="1635668255065"></p>
</summary>
<category term="算法" scheme="http://www.yulezhang.com/categories/%E7%AE%97%E6%B3%95/"/>
</entry>
<entry>
<title>腾讯字节实习面试总结</title>
<link href="http://www.yulezhang.com/2021/09/03/69InternSummary/"/>
<id>http://www.yulezhang.com/2021/09/03/69InternSummary/</id>
<published>2021-09-03T05:10:00.000Z</published>
<updated>2021-09-06T02:32:11.044Z</updated>
<summary type="html">
<p>近期想找一份关于后台开发的实习，全力准备了一个半月的算法，当前此前也有零碎的刷题。然后就直接投简历了，收到腾讯和字节两家面试通知，面试问题如下。</p>
<h3 id="腾讯">腾讯</h3>
<p>腾讯面经，部门主要是做AI算法的呈现</p>
</summary>
<category term="实习" scheme="http://www.yulezhang.com/categories/%E5%AE%9E%E4%B9%A0/"/>
<category term="随笔" scheme="http://www.yulezhang.com/tags/%E9%9A%8F%E7%AC%94/"/>
</entry>
<entry>
<title>力扣排列组合问题梳理（超详细）</title>
<link href="http://www.yulezhang.com/2021/09/02/68CombinationLeetcode/"/>
<id>http://www.yulezhang.com/2021/09/02/68CombinationLeetcode/</id>
<published>2021-09-02T06:56:00.000Z</published>
<updated>2021-09-03T05:09:34.743Z</updated>
<summary type="html">
<blockquote>
<p>说明：本文基于慕课《<a href="https://coding.imooc.com/class/82.html">玩转算法面试 从真题到思维全面提升算法思维</a>》，并加入了一些自己的理解。</p>
</blockquote>
<h2 id="递归与回溯框架">递归与回溯框架</h2>
<p>对于递归本身，可以结合二叉树的性质去理解，不是本文讨论的重点。本文讨论了更一般的递归问题和回溯的算法思想，这些问题在本质上也属于树形问题。顾名思义，对于问题解的讨论可以用一颗树来进行表示。来看一些例题</p>
</summary>
<category term="算法" scheme="http://www.yulezhang.com/categories/%E7%AE%97%E6%B3%95/"/>
<category term="leetcode" scheme="http://www.yulezhang.com/tags/leetcode/"/>
</entry>
<entry>
<title>TGen-NU model fusion</title>
<link href="http://www.yulezhang.com/2021/05/02/66CodeDetect/"/>
<id>http://www.yulezhang.com/2021/05/02/66CodeDetect/</id>
<published>2021-05-02T12:46:00.000Z</published>
<updated>2021-09-03T05:37:20.721Z</updated>
<summary type="html">
<p>本周工作</p>
<ul>
<li>TGAN生成X-ray图片</li>
<li>GenPU生成X-ray图片</li>
<li>设计<strong>TGen-NU</strong>模型，并尝试生成X-ray图片</li>
<li>解决归一化问题<sup>[1]</sup></li>
<li>基本完成TGen-NU的生成任务，但仍存在<strong>不稳定、不收敛</strong>问题<sup>[2]</sup></li>
<li>查阅学习GAN的公式推导、扩展资料如<strong>WGAN、DCGAN</strong>等</li>
<li>新思路：把MPS融入到GenPU/TGen-NU模型中</li>
</ul>
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="实验复现" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E5%AE%9E%E9%AA%8C%E5%A4%8D%E7%8E%B0/"/>
</entry>
<entry>
<title>TGAN and GenPU</title>
<link href="http://www.yulezhang.com/2021/04/23/65TGAN-GenPU/"/>
<id>http://www.yulezhang.com/2021/04/23/65TGAN-GenPU/</id>
<published>2021-04-23T02:35:00.000Z</published>
<updated>2021-09-03T05:37:34.000Z</updated>
<summary type="html">
<h3 id="bilibili-robust-low-tubal-rank-tensor-recovery-from-binary-measurements">【<a href="https://www.bilibili.com/s/video/BV1QK4y1N7dp">bilibili</a>】<strong>Robust Low-tubal-rank Tensor Recovery from Binary Measurements</strong></h3>
<p>在看这个视频时，顺带又回顾了一下张量秩的概念，目前并没有给出统一的很明确的定义，张量秩的定义往往跟分解算法有关</p>
<p>在CP分解中，张量的秩定义如下</p>
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="理论基础" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E7%90%86%E8%AE%BA%E5%9F%BA%E7%A1%80/"/>
</entry>
<entry>
<title>FCTN-Decomposition-Code</title>
<link href="http://www.yulezhang.com/2021/04/18/64FCTN-Code-Analysis/"/>
<id>http://www.yulezhang.com/2021/04/18/64FCTN-Code-Analysis/</id>
<published>2021-04-18T12:59:00.000Z</published>
<updated>2021-09-03T05:37:46.000Z</updated>
<summary type="html">
<p>本周主要是想抓紧把之前TTN和MPO作用batch的思路落实一下，并理解FCTN的matlab代码</p>
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="实验复现" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E5%AE%9E%E9%AA%8C%E5%A4%8D%E7%8E%B0/"/>
</entry>
<entry>
<title>FCTN-Decomposition</title>
<link href="http://www.yulezhang.com/2021/04/11/63FCTN-Decomposition/"/>
<id>http://www.yulezhang.com/2021/04/11/63FCTN-Decomposition/</id>
<published>2021-04-11T02:41:00.000Z</published>
<updated>2021-09-03T05:37:56.000Z</updated>
<summary type="html">
<p>本周花了大量时间精读FCTN，还联系上了原作者郑博士，弄懂了论文中的公式推到部分。 同时这次的学习也将之前忽略的很多细节也抓了起来，比如参数复杂度、计算复杂度等等，不提高自己对公式的理解是没法提高论文的档次的，这篇文章的公式恰好不是很难，便于入门。</p>
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="理论基础" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E7%90%86%E8%AE%BA%E5%9F%BA%E7%A1%80/"/>
</entry>
<entry>
<title>量子机器学习资料整理</title>
<link href="http://www.yulezhang.com/2021/03/28/62QML-Collections/"/>
<id>http://www.yulezhang.com/2021/03/28/62QML-Collections/</id>
<published>2021-03-28T12:50:00.000Z</published>
<updated>2021-09-03T05:18:32.356Z</updated>
<summary type="html">
<p>由于目前张量网络的工作逐渐增多，很多实验室都封装了自己的张量收缩算法包，同时还有一些论文给出了具体的工作，在此归类梳理一下方便日后的学习。</p>
<h2 id="workshop">Workshop</h2>
<ul>
<li><a href="https://tensorworkshop.github.io/2020/index.html"><strong>IJCAL</strong></a>: International Workshop on Tensor Network Representations in Machine Learning</li>
<li><a href="https://tensorworkshop.github.io/NeurIPS2020/"><strong>NeurIPS2020</strong></a>: Quantum tensor networks in machine learning</li>
<li><a href="http://ipam.ucla.edu/wp-content/uploads/2019/09/TMWS2-Poster.pdf">ipam</a>: Tensor Network States and Applications, <strong>APRIL 19 - 23, 2021</strong></li>
</ul>
</summary>
<category term="资料整理" scheme="http://www.yulezhang.com/categories/%E8%B5%84%E6%96%99%E6%95%B4%E7%90%86/"/>
</entry>
<entry>
<title>《智能时代》读书笔记</title>
<link href="http://www.yulezhang.com/2021/03/27/60ReadBook/"/>
<id>http://www.yulezhang.com/2021/03/27/60ReadBook/</id>
<published>2021-03-27T13:15:14.000Z</published>
<updated>2021-09-03T05:57:39.112Z</updated>
<summary type="html">
<p>总结了一下华为软挑比赛，同时整理了一下<a href="http://www.yulezhang.com/2021/03/28/62QML-Collections/">量子机器学习的代码学习资料</a>，并对二维MERA结构进行了数据集拓展、阅读《智能时代》。</p>
</summary>
<category term="读书笔记" scheme="http://www.yulezhang.com/categories/%E8%AF%BB%E4%B9%A6%E7%AC%94%E8%AE%B0/"/>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
</entry>
<entry>
<title>华为软件精英挑战赛</title>
<link href="http://www.yulezhang.com/2021/03/27/61HuaweiSoftwareContest/"/>
<id>http://www.yulezhang.com/2021/03/27/61HuaweiSoftwareContest/</id>
<published>2021-03-27T10:00:00.000Z</published>
<updated>2021-09-03T05:26:12.543Z</updated>
<summary type="html">
<p>能够承认自己的普通并非易事</p>
</summary>
<category term="随笔" scheme="http://www.yulezhang.com/categories/%E9%9A%8F%E7%AC%94/"/>
</entry>
<entry>
<title>HHL and TEBD</title>
<link href="http://www.yulezhang.com/2021/03/20/59CodeBreakthrough/"/>
<id>http://www.yulezhang.com/2021/03/20/59CodeBreakthrough/</id>
<published>2021-03-20T00:33:14.000Z</published>
<updated>2021-09-03T05:38:18.000Z</updated>
<summary type="html">
<p>本周汇报目前将分为以下三个部分</p>
<h1>量子算法回顾</h1>
<p>在周二下午的汇报之后发现对量子<strong>傅里叶变换、量子相位估计算法、Shor以及HHL算法</strong>理解的还不够透彻，下面列出了一些遗留的疑难问题的讨论和补充。汇报PPT点击<a href="/download/QuantumAlgorithm/20190721-%E9%87%8F%E5%AD%90%E7%AE%97%E6%B3%95%E4%B8%93%E9%A2%98-%E5%BC%A0%E5%AE%87.pptx">此处</a>下载</p>
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="理论基础" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E7%90%86%E8%AE%BA%E5%9F%BA%E7%A1%80/"/>
</entry>
<entry>
<title>Grover</title>
<link href="http://www.yulezhang.com/2021/03/14/58Grover/"/>
<id>http://www.yulezhang.com/2021/03/14/58Grover/</id>
<published>2021-03-14T13:21:17.000Z</published>
<updated>2021-09-03T05:38:24.627Z</updated>
<summary type="html">
<p><strong>Grover算法</strong></p>
<p>搜索算法是利用计算机的高性能来有目的的穷举一个问题解空间的部分或所有的可能情况，从而求出问题的解的一种方法。现阶段一般有枚举算法、深度优先搜索、广度优先搜索、A*算法、回溯算法、蒙特卡洛树搜索、散列函数等算法。比较常见的一种应用场景就是A到B的最短耗时路径搜索，一般的传统方法我们至少要把所有的路径遍历一遍来求解，而量子Grover算法只需要<span class="katex"><span class="katex-mathml"><math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi>O</mi><mo stretchy="false">(</mo><msqrt><mo stretchy="false">(</mo></msqrt><mi>n</mi><mo stretchy="false">)</mo><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">O(\sqrt(n))</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:1.24em;vertical-align:-0.30499999999999994em;"></span><span class="mord mathdefault" style="margin-right:0.02778em;">O</span><span class="mopen">(</span><span class="mord sqrt"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.935em;"><span class="svg-align" style="top:-3.2em;"><span class="pstrut" style="height:3.2em;"></span><span class="mopen" style="padding-left:1em;">(</span></span><span style="top:-2.8950000000000005em;"><span class="pstrut" style="height:3.2em;"></span><span class="hide-tail" style="min-width:1.02em;height:1.28em;"><svg width='400em' height='1.28em' viewBox='0 0 400000 1296' preserveAspectRatio='xMinYMin slice'><path d='M263,681c0.7,0,18,39.7,52,119
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c-22.3,46.7,-33.8,70.3,-34.5,71c-4.7,4.7,-12.3,7,-23,7s-12,-1,-12,-1
s-109,-253,-109,-253c-72.7,-168,-109.3,-252,-110,-252c-10.7,8,-22,16.7,-34,26
c-22,17.3,-33.3,26,-34,26s-26,-26,-26,-26s76,-59,76,-59s76,-60,76,-60z
M1001 80h400000v40h-400000z'/></svg></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.30499999999999994em;"><span></span></span></span></span></span><span class="mord mathdefault">n</span><span class="mclose">)</span><span class="mclose">)</span></span></span></span>的复杂度就能解决该问题。</p>
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="理论基础" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E7%90%86%E8%AE%BA%E5%9F%BA%E7%A1%80/"/>
</entry>
<entry>
<title>TNML-ACML2020Tutorial</title>
<link href="http://www.yulezhang.com/2021/03/07/57TNML-ACML2020Tutorial/"/>
<id>http://www.yulezhang.com/2021/03/07/57TNML-ACML2020Tutorial/</id>
<published>2021-03-07T14:21:17.000Z</published>
<updated>2021-09-03T05:38:35.778Z</updated>
<summary type="html">
<p><strong>第38页</strong></p>
<p>Knowledge Distillation (Hinton et al., NIPS 2014 Workshop)</p>
<p>Quantization and Sharing of Weight (Han et al., ICLR 2016)</p>
<p>Low-rank Matrix/Tensor Factorization (Novikov et al., NIPS 2015)</p>
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="理论基础" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E7%90%86%E8%AE%BA%E5%9F%BA%E7%A1%80/"/>
</entry>
<entry>
<title>寒假学习汇报</title>
<link href="http://www.yulezhang.com/2021/02/28/56WinterVacation/"/>
<id>http://www.yulezhang.com/2021/02/28/56WinterVacation/</id>
<published>2021-02-28T13:39:17.000Z</published>
<updated>2021-09-03T05:38:48.000Z</updated>
<summary type="html">
Welcome to my blog, it's a secret, please enter password to read.
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="理论基础" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E7%90%86%E8%AE%BA%E5%9F%BA%E7%A1%80/"/>
</entry>
<entry>
<title>Writing material</title>
<link href="http://www.yulezhang.com/2021/01/05/55WritingCorpus/"/>
<id>http://www.yulezhang.com/2021/01/05/55WritingCorpus/</id>
<published>2021-01-05T12:37:17.000Z</published>
<updated>2021-09-03T05:39:16.000Z</updated>
<summary type="html">
<p>This essay are used to collect excellent sentences or vocabularies in paper writing releated to machine learning.</p>
<h1>Sentences</h1>
<h2 id="describe-our-method">Describe our method</h2>
<ul>
<li>In this section, we evaluate the superior aspects as well as the limitations of the proposed model by taking into account the state-of-art models</li>
<li>The results show that EVGO outperforms all the algorithms in comparison for all experiments.</li>
</ul>
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="论文写作" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E8%AE%BA%E6%96%87%E5%86%99%E4%BD%9C/"/>
<category term="语料" scheme="http://www.yulezhang.com/tags/%E8%AF%AD%E6%96%99/"/>
</entry>
<entry>
<title>学堂在线---《如何写好科研论文》秋</title>
<link href="http://www.yulezhang.com/2020/12/14/52PaperWriting/"/>
<id>http://www.yulezhang.com/2020/12/14/52PaperWriting/</id>
<published>2020-12-14T14:21:12.000Z</published>
<updated>2021-09-03T05:39:58.295Z</updated>
<summary type="html">
<p>学堂在线—<a href="https://www.xuetangx.com/learn/THU04011000365/THU04011000365/4233659/video/6387967">《如何写好科研论文》秋</a></p>
<p>连续阅读相关方向的论文，做一定的积累，一天一篇或者两天一篇，最重要的是感觉不能断，将阅读过程中的一些想法记录下来，同方向的一些经典文章要精读(最少读5遍以上)</p>
</summary>
<category term="周汇报" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/"/>
<category term="论文写作" scheme="http://www.yulezhang.com/categories/%E5%91%A8%E6%B1%87%E6%8A%A5/%E8%AE%BA%E6%96%87%E5%86%99%E4%BD%9C/"/>
</entry>
<entry>
<title>深度学习小结</title>
<link href="http://www.yulezhang.com/2020/12/08/51DeepLearning/"/>
<id>http://www.yulezhang.com/2020/12/08/51DeepLearning/</id>
<published>2020-12-08T12:21:12.000Z</published>
<updated>2021-09-03T05:20:44.192Z</updated>
<summary type="html">
<p>我接触深度学习已经有一段时间了，特别是现在读研究生还是离不开机器学习这方面的内容，因此我需要不断地提高这方面的水平，每一次编码都要比以往更加<strong>规范、高效并提高封装效果</strong>以便于快速的进行二次开发，而不能仅仅水平一直停留在<strong>复制粘贴、调包</strong>的程度，很多小工具需要弄清出工作原理，不一定都要复现，但出了问题一定要第一时间能够修改和调试。</p>
</summary>
<category term="算法" scheme="http://www.yulezhang.com/categories/%E7%AE%97%E6%B3%95/"/>
</entry>
</feed>