【演講】2019/11/19 (二) @工四816 (智易空間),邀請到Prof. Geoffrey Li(Georgia Tech, USA)與Prof. Li-Chun Wang(NCTU, Taiwan) 演講「Deep Learning based Wireless Resource Allocation/Deep Learning in Physical Layer Communications/Machine Learning Interference Management」
IBM中心特別邀請到Prof. Geoffrey Li(Georgia Tech, USA)與Prof. Li-Chun Wang(NCTU, Taiwan)前來為我們演講,歡迎有興趣的老師與同學報名參加!
演講標題:Deep Learning based Wireless Resource Allocation/Deep Learning in Physical Layer Communications/Machine Learning Interference Management
演 講 者:Prof. Geoffrey Li與Prof. Li-Chun Wang
時 間:2019/11/19(二) 9:00 ~ 12:00
地 點:交大工程四館816 (智易空間)
活動報名網址:https://forms.gle/vUr3kYBDB2vvKtca6
報名方式:
費用:(費用含講義、午餐及茶水)
1.費用:(1) 校內學生免費,校外學生300元/人 (2) 業界人士與老師1500/人
2.人數:60人,依完成報名順序錄取(完成繳費者始完成報名程序)
※報名及繳費方式:
1.報名:請至報名網址填寫資料
2.繳費:
(1)親至交大工程四館813室完成繳費(前來繳費者請先致電)
(2)匯款資訊如下:
戶名: 曾紫玲(國泰世華銀行 竹科分行013)
帳號: 075506235774 (國泰世華銀行 竹科分行013)
匯款後請提供姓名、匯款時間以及匯款帳號後五碼以便對帳
※將於上課日發放課程繳費領據
聯絡方式:曾紫玲 Tel:03-5712121分機54599 Email:tzuling@nctu.edu.tw
Abstract:
1.Deep Learning based Wireless Resource Allocation
【Abstract】
Judicious resource allocation is critical to mitigating interference, improving network efficiency, and ultimately optimizing wireless network performance. The traditional wisdom is to explicitly formulate resource allocation as an optimization problem and then exploit mathematical programming to solve it to a certain level of optimality. However, as wireless networks become increasingly diverse and complex, such as high-mobility vehicular networks, the current design methodologies face significant challenges and thus call for rethinking of the traditional design philosophy. Meanwhile, deep learning represents a promising alternative due to its remarkable power to leverage data for problem solving. In this talk, I will present our research progress in deep learning based wireless resource allocation. Deep learning can help solve optimization problems for resource allocation or can be directly used for resource allocation. We will first present our research results in using deep learning to solve linear sum assignment problems (LSAP) and reduce the complexity of mixed integer non-linear programming (MINLP), and introduce graph embedding for wireless link scheduling. We will then discuss how to use deep reinforcement learning directly for wireless resource allocation with application in vehicular networks.
2.Deep Learning in Physical Layer Communications
【Abstract】
It has been demonstrated recently that deep learning (DL) has great potentials to break the bottleneck of the conventional communication systems. In this talk, we present our recent work in DL in physical layer communications. DL can improve the performance of each individual (traditional) block in the conventional communication systems or jointly optimize the whole transmitter or receiver. Therefore, we can categorize the applications of DL in physical layer communications into with and without block processing structures. For DL based communication systems with block structures, we present joint channel estimation and signal detection based on a fully connected deep neural network, model-drive DL for signal detection, and some experimental results. For those without block structures, we provide our recent endeavors in developing end-to-end learning communication systems with the help of deep reinforcement learning (DRL) and generative adversarial net (GAN). At the end of the talk, we provide some potential research topics in the area.
3.Machine Learning Interference Management
【Abstract】
In this talk, we discuss how machine learning algorithms can address the performance issues of high-capacity ultra-dense small cells in an environment with dynamical traffic patterns and time-varying channel conditions. We introduce a bi adaptive self-organizing network (Bi-SON) to exploit the power of data-driven resource management in ultra-dense small cells (UDSC). On top of the Bi-SON framework, we further develop an affinity propagation unsupervised learning algorithm to improve energy efficiency and reduce interference of the operator deployed and the plug-and-play small cells, respectively. Finally, we discuss the opportunities and challenges of reinforcement learning and deep reinforcement learning (DRL) in more decentralized, ad-hoc, and autonomous modern networks, such as Internet of things (IoT), vehicle -to-vehicle networks, and unmanned aerial vehicle (UAV) networks.
Bio:
Dr. Geoffrey Li is a Professor with the School of Electrical and Computer Engineering at Georgia Institute of Technology. He was with AT&T Labs – Research for five years before joining Georgia Tech in 2000. His general research interests include statistical signal processing and machine learning for wireless communications. In these areas, he has published around 500 referred journal and conference papers in addition to over 40 granted patents. His publications have cited by 37,000 times and he has been listed as the World’s Most Influential Scientific Mind, also known as a Highly-Cited Researcher, by Thomson Reuters almost every year since 2001. He has been an IEEE Fellow since 2006. He received 2010 IEEE ComSoc Stephen O. Rice Prize Paper Award, 2013 IEEE VTS James Evans Avant Garde Award, 2014 IEEE VTS Jack Neubauer Memorial Award, 2017 IEEE ComSoc Award for Advances in Communication, and 2017 IEEE SPS Donald G. Fink Overview Paper Award. He also won the 2015 Distinguished Faculty Achievement Award from the School of Electrical and Computer Engineering, Georgia Tech.
Li-Chun Wang (M'96 -- SM'06 -- F'11) received Ph. D. degree from the Georgia Institute of Technology, Atlanta, in 1996. From 1996 to 2000, he was with AT&T Laboratories, where he was a Senior Technical Staff Member in the Wireless Communications Research Department. Currently, he is the Chair Professor of the Department of Electrical and Computer Engineering and the Director of Big Data Research Center of of National Chiao Tung University in Taiwan. Dr. Wang was elected to the IEEE Fellow in 2011 for his contributions to cellular architectures and radio resource management in wireless networks. He was the co-recipients of IEEE Communications Society Asia-Pacific Board Best Award (2015), Y. Z. Hsu Scientific Paper Award (2013), and IEEE Jack Neubauer Best Paper Award (1997). He won the Distinguished Research Award of Ministry of Science and Technology in Taiwan twice (2012 and 2016). He is currently the associate editor of IEEE Transaction on Cognitive Communications and Networks. His current research interests are in the areas of software-defined mobile networks, heterogeneous networks, and data-driven intelligent wireless communications. He holds 23 US patents, and have published over 300 journal and conference papers, and co-edited a book, “Key Technologies for 5G Wireless Systems,” (Cambridge University Press 2017).
同時也有3部Youtube影片,追蹤數超過37萬的網紅Ray Mak,也在其Youtube影片中提到,Back in the days, before YouTube was founded, before most of you were born, I used to Vlog a lot. I was a little ahead of my time because video sharin...
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- Bậc học: Thạc sỹ + Tiến sỹ
- Deadline: Tháng 10 (annual)
3. ETH Zurich Excellence Masters Scholarships
- Quốc gia: Thụy Sỹ
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- Deadline: Tháng 12 (annual)
4. Global Undergraduate Exchange Program (Global UGRAD)
- Quốc gia: USA
- Bậc học: Chương trình trao đổi
- Deadline: Tháng 12 (annual)
5. Leiden University Excellence Scholarships (LexS)
- Quốc gia: Hà lan
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- Quốc gia: Anh
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- Deadline: Tháng 10 (annual)
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cambridge university usa 在 喬的英文筆記 Joe's English Learning Notes Facebook 的最讚貼文
再次分享學習資源彙整
--
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【喬的部落格網誌聊英文談職場/商務英文】
☛ Blogger: http://ohjoseph86.blogspot.com/
【快追蹤IG關注第一手更新與喬生活】
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<英語學習資源大集錦分享!字典/新聞/科學/經濟/綜合類>
喬今天要分享的是英語學習資源大集錦,超多連結替各位整理好在這,其中不乏喬本身超愛用的網站,在此分享給大家!
【字典類】
(1) Cambridge Dictionaries Online 劍橋線上字典(美式/英式發音) http://dictionary.cambridge.org/
(2) Dictionary.com 許多查不到的字這都有
http://dictionary.reference.com/
(3) The Free Dictionary 這裡可查詢到許多專有名詞
http://www.thefreedictionary.com/
(4) Urban Dictionary 當代俚語解釋網站
http://www.urbandictionary.com/
(5) Oxford Dictionary: 有趣的網站,會解答許多關於”字彙”的故事
http://www.oxforddictionaries.com/
(6) The Online Slang Dictionary 柏客萊大學的俚語字典
https://www.ocf.berkeley.edu/~wrader/
【綜合推薦類】
(1) 美國百大名校開放課程:
http://www.baidaonline.com/index.php
(2) Debatable(作文題目網站)
http://idebate.org/debatabase
(3) VoiceTube(看影片學英語):
http://tw.blog.voicetube.com/
(4) ESL Learning for Traveling Students 留學生實用英語網站
https://www.kanetix.ca/esl-learning-for-traveling-students
(5) 美國校園俚語集合
http://www.angelfire.com/…/html-o…/usa-schoolslang/index.htm
(6) 名詞與其表達意義
http://www.homepagers.com/names/
(7) 英文文學相關資源(豐富連結)
http://andromeda.rutgers.edu/~jlynch/Lit/
(8) 收集相當多電子文本的網站
http://digital.library.upenn.edu/books/
(9) 歷史悠久的線上文學電子本免費網站
http://www.gutenberg.org/wiki/Main_Page
(10) 電影對白相關網站,此網站具有強大字幕資料庫建檔
http://subsmax.com/
(11) 電影劇本網站
http://www.awesomefilm.com/
(12) 眾多英文文法中,一般人常犯錯誤列表
http://public.wsu.edu/~brians/errors/index.html
(13) 實用英文寫作
http://www.1-language.com/
(14) 美國普渡大學(Purdue University)提供的線上英文寫作資源
https://owl.english.purdue.edu/
(15) 美國伊若斯大學(University of Illinois)提供線上英文寫作資源
http://www.cws.illinois.edu/workshop/
(16) 實用英文寫作形容詞列表集合
http://www.keepandshare.com/…/adjective-list-adjectives-list
(17) 多義字集合網站
http://www-personal.umich.edu/~cellis/heteronym.html
(18) 矛盾字集合網站
http://www-personal.umich.edu/~cellis/antagonym.html
(19) 有聲書聽講網站
http://www.storynory.com/
(20) Open Culture (線上英語教學媒體)
http://www.openculture.com/
(21) 類Youtube,提供許多幽默短片
http://www.videojug.com/
(22) 超過一千種英文聽力單元的網站
http://www.elllo.org/english/home.htm
(23) 英語會話網站,資料庫豐富,但無語音
http://www.english-at-home.com/speaking/
(24) 提供各程度的英語聽力測驗
http://www.esl-lab.com/
(25) American Accent A-Z 線上發音商業網站
http://www.americanaccent.com/
(26) 線上英文發音網站(有豐富的資料庫)
http://faculty.washington.edu/…/PhonReso…/PhonResources.html
(27) Interpals 教筆友的網站,有點像Facebook
http://www.interpals.net/
【科學類】
(1) Scientific American 60 Second系列:
60 Second Science- goo.gl/5NAmRN
60 Second Space- goo.gl/wcAlCR
60 Second Earth- goo.gl/t2aXnZ
60 Second Tech- goo.gl/X3qIaT
60 Second Mind- goo.gl/gnvmCx
60 Second Health- goo.gl/A24iQW
(2)National Geographic
http://www.nationalgeographic.com/
(3) Discovery-
https://www.discovery.com/
(4) HowStuffWorks
http://www.howstuffworks.com/
(5) NASA
http://www.nasa.gov/
(6) LiveScience
http://www.livescience.com/
(7) ScienceDaily
http://www.sciencedaily.com/
(8) ScienceDirect
http://www.sciencedirect.com/
(9) Space
http://www.space.com/
(10) Nature
http://www.nature.com/
(11) Popsci
http://www.popsci.com/
(12) Smithsonian
http://www.smithsonianmag.com/ist/?next=/
(13) Treehugger
http://www.treehugger.com/
(14) NewScientist
http://www.newscientist.com/
(15) redOrbit
http://www.redorbit.com/
(16) NIH (National Institute of Health)
http://www.nih.gov/
(17) WebMD
http://www.webmd.com/
【新聞/演講類】
(1) TED- https://www.ted.com/
(推薦APP- TuneIn Radio讓在手機上聽TED相當容易)
(2) CNN-
http://edition.cnn.com/
(3) The Times-
http://www.thetimes.co.uk/tto/news/
(4) BBC News-
http://www.bbc.com/
(5) NewsWeek 美國新聞周刊
http://www.newsweek.com/
(6) Public Broadcasting Service 美國公共電視
http://www.pbs.org/
(7) 美國政府提供經濟、政治相關領域報導的網站
http://iipdigital.usembassy.gov/#axzz3VvBY07QV
(8) HuffingtonPost
http://www.huffingtonpost.com/
(9) FoxNews
http://www.foxnews.com/
(10) Mail Online
http://www.dailymail.co.uk/home/index.html
(11) NBC News
http://www.nbcnews.com/
(12) The Guardian
http://www.theguardian.com/uk
(13) ABCNews
http://abcnews.go.com/
(14) USA Today
http://www.usatoday.com/
(15) LATimes
http://www.latimes.com/
【商業/財金/經濟類】
(1) The Economist 經濟學人雜誌-
http://www.economist.com/
(2) The Economist Times-
http://economictimes.indiatimes.com/
(3)HarvardBusinessSchool-
http://hbswk.hbs.edu/workingpapers/
(4) Forbes-
http://www.forbes.com/
(5) CNNMoney-
http://money.cnn.com/
(6) WSJ(Wall Street Journal)
http://www.wsj.com/
(7) Yahoo! Finance
http://finance.yahoo.com/
(8) Google Finance
https://www.google.com/finance
(9) Bloomberg Business
http://www.bloomberg.com/
(10) CNBC International
http://www.cnbc.com/
(11) The Motley Fool
http://www.fool.com/
(12) BusinessInsider
http://www.businessinsider.com/
(13) Marketwatch
http://www.marketwatch.com/
(14) Finantial Times
htttp://www.ft.com
(15) Seeking Alpha
http://seekingalpha.com/
(16) IBTimes
http://www.ibtimes.com/
(17) cNet
http://www.cnet.com/
(18) Mashable
http://mashable.com/
(19) Techcrunch
http://techcrunch.com/
(20) Wired
http://www.wired.com/
(21) ZDNet
http://www.zdnet.com/
(22) Webpronews
http://www.webpronews.com/
(23) Arstechnica
http://arstechnica.com/
(24) VentureBeat
http://venturebeat.com/
(25) Thenextweb
http://thenextweb.com/
(26) Gigaom
https://gigaom.com/
(27) Informationweek
http://www.informationweek.com/
(28) Sitepoint
http://www.sitepoint.com/
(29) Readwrite
http://readwrite.com/
(30) Searchengineland
http://searchengineland.com/
(31) DigitalPoint
https://forums.digitalpoint.com/
cambridge university usa 在 Ray Mak Youtube 的最佳貼文
Back in the days, before YouTube was founded, before most of you were born, I used to Vlog a lot. I was a little ahead of my time because video sharing platforms were premature back then. I Vlogged so that I can remember my experiences back then. You'll get to know me better if you actually spend the time to watch this. If you do have the patience.
By the way, during this time, even Facebook was only available for selected University Students in US with emails ending .edu
I spoke mostly Cantonese in this video (My Mother Tongue), be sure to turn on captions.
Year : 2005
Location : Cambridge, Massachusetts
Fan-Made Intro by Nitro77
https://www.youtube.com/channel/UCJd9-C_iZGriWwrRKPYODyQ
(Make me a nice short intro using the same audio and I'll feature you next)
?SHEET MUSIC & Mp3 ▸ http://www.makhonkit.com
?LEARN MY SONGS ▸ https://tinyurl.com/RayMak-flowkey
?Listen on Spotify ▸ https://sptfy.com/raymak
?Listen on Apple Music ▸ https://music.apple.com/sg/artist/ray-mak/1498802526
?Full Song List ▸ http://www.redefiningpiano.com
Talk to me :
? Instagram ▸ http://instagram.com/makhonkit
? Facebook ▸ http://facebook.com/raymakpiano
? Twitter ▸ http://twitter.com/makhonkit
#vlog #cambridge #USA
cambridge university usa 在 Elaine Hau Youtube 的精選貼文
Please check out my business Luxury Fashion Rentals, a luxury handbag rental e-commerce website: https://luxuryfashionrentals.com
中文字幕請打開[字幕](右下方):)
如果仍然看不到中文字幕,請轉到“設置”(右下方),然後轉到“字幕”,然後“自動翻譯”,然後點擊“中文”
Please turn on [CC] for English subtitles :)
If you still can't see English subtitles, then go to "Settings", then "Subtitles/CC", then "English"
中文字幕请打开[字幕] (右下方) :)
如果仍然看不到中文字幕,请转到“设置”(右下方),然后转到“字幕”,然后"自动翻译",然后点击“中文”
**這不是一個贊助的視頻,我用我自己的錢購買的。
**This video is not sponsored. I purchased the items with my own money.
**这不是一个赞助的视频,我用我自己的钱购买的。
感謝您的收看!
Thank you for watching!!
感谢您的收看!
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cambridge university usa 在 MYBY孟言布语 Youtube 的精選貼文
Dayday's Social Media
Instagram: Dayday_boy
Weibo: 孟天Wiley
Snapchat: Hellodayday
Blair's Social Media:
Instagram: Blairsugarman1
Weibo: @英国布莱尔
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Weibo:MYBY孟言布语
微信公众号:孟言布语
这一期DAYDAY和黄布要聊聊他们自己国家的中餐VS国内的中国菜。
In this episode Dayday and Blair talking Chinese food in their own countries vs mainland China.
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