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GoogleBot | / | ✔ |
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Title | Yu Yang’s Home |
Description | HOME BLOG RESEARCH LOG CV PACKAGE TEACHING COURSES STAT 8051 STAT 8052 STAT 8111/2 IE 8521 STAT 8054 Yu Yang Ph.D. candidate in Statistics I am a Ph.D. ca |
Keywords | N/A |
WebSite | yuyangyy.com |
Host IP | 185.199.110.153 |
Location | - |
Site | Rank |
US$1,592
Last updated: 2023-05-20 06:54:29
yuyangyy.com has Semrush global rank of 0. yuyangyy.com has an estimated worth of US$ 1,592, based on its estimated Ads revenue. yuyangyy.com receives approximately 183 unique visitors each day. Its web server is located in -, with IP address 185.199.110.153. According to SiteAdvisor, yuyangyy.com is safe to visit. |
Purchase/Sale Value | US$1,592 |
Daily Ads Revenue | US$1 |
Monthly Ads Revenue | US$44 |
Yearly Ads Revenue | US$529 |
Daily Unique Visitors | 12 |
Note: All traffic and earnings values are estimates. |
Host | Type | TTL | Data |
yuyangyy.com. | A | 3599 | IP: 185.199.110.153 |
yuyangyy.com. | A | 3599 | IP: 185.199.109.153 |
yuyangyy.com. | A | 3599 | IP: 185.199.111.153 |
yuyangyy.com. | A | 3599 | IP: 185.199.108.153 |
yuyangyy.com. | NS | 21600 | NS Record: ns-cloud-d1.googledomains.com. |
yuyangyy.com. | NS | 21600 | NS Record: ns-cloud-d2.googledomains.com. |
yuyangyy.com. | NS | 21600 | NS Record: ns-cloud-d4.googledomains.com. |
yuyangyy.com. | NS | 21600 | NS Record: ns-cloud-d3.googledomains.com. |
HOME BLOG RESEARCH LOG CV PACKAGE TEACHING COURSES STAT 8051 STAT 8052 STAT 8111/2 IE 8521 STAT 8054 Yu Yang Ph.D. candidate in Statistics I am a Ph.D. candidate in Statistics. I am always hungry to learn. I am interested in natural language processing and causal discovery. My motto is: Respect Life! Featured Projects Here are some selected projects that I have done. More projects can be found at my Github . Topic-Aware Text Summarization This is a demo project to investigate the effectiveness of using text RBM to insert topic information to summarization models. Github repo Final report Slides Retro-BiDAF: A Retrospective Reader Over BiDAF For the SQuAD 2.0 Challenge, I combined the idea of retrospective reading and BiDAF and proposed the Retro-BiDAF model, which improved both the EM and F1 score in the non-PCE scenario. Github repo Final report Slides Kaggle: Lyft Motion Prediction for Autonomous Vehicles This Kaggle competition was supported by Lyft and the goal was to build a |
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