找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Machine Learning with Quantum Computers; Maria Schuld,Francesco Petruccione Book 2021Latest edition The Editor(s) (if applicable) and The

[復(fù)制鏈接]
樓主: aspirant
11#
發(fā)表于 2025-3-23 13:28:22 | 只看該作者
Potential Quantum Advantages,irst have a closer look at different criteria for a quantum advantage, and then consider data mining on coherent or “quantum data”. We finally summarise some future perspectives for quantum machine learning research as a concluding outlook.
12#
發(fā)表于 2025-3-23 14:51:40 | 只看該作者
13#
發(fā)表于 2025-3-23 18:53:30 | 只看該作者
14#
發(fā)表于 2025-3-23 23:10:45 | 只看該作者
15#
發(fā)表于 2025-3-24 04:21:21 | 只看該作者
16#
發(fā)表于 2025-3-24 07:09:00 | 只看該作者
Machine Learning,ell as the basic concepts of training, regularisation and generalisation. A number of important models—such as linear models, neural networks, probabilistic graphical models and kernel methods—are introduced as a foundation and reference for later chapters.
17#
發(fā)表于 2025-3-24 11:34:02 | 只看該作者
18#
發(fā)表于 2025-3-24 15:45:39 | 只看該作者
Representing Data on a Quantum Computer,etimes an entire dataset, can be encoded into quantum states. We present quantum routines for this task, discuss their runtimes and review their interpretation as feature maps known in classical machine learning.
19#
發(fā)表于 2025-3-24 20:23:02 | 只看該作者
20#
發(fā)表于 2025-3-25 00:19:43 | 只看該作者
Potential Quantum Advantages,irst have a closer look at different criteria for a quantum advantage, and then consider data mining on coherent or “quantum data”. We finally summarise some future perspectives for quantum machine learning research as a concluding outlook.
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-12 05:46
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
山丹县| 宁明县| 临沭县| 康马县| 长春市| 林州市| 稻城县| 庆元县| 盈江县| 海城市| 琼海市| 三穗县| 阜康市| 积石山| 连山| 上虞市| 西平县| 会东县| 克什克腾旗| 九龙坡区| 五常市| 莱州市| 隆昌县| 西昌市| 崇信县| 堆龙德庆县| 龙南县| 蓬莱市| 噶尔县| 广灵县| 新绛县| 晋州市| 顺义区| 天津市| 新民市| 冀州市| 阿尔山市| 上林县| 绥阳县| 黔江区| 济南市|