Robot | Path | Permission |
GoogleBot | / | ✔ |
BingBot | / | ✔ |
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Title | Eren C. |
Description | Eren C. Kızıldağ e-mail : eck2170@columbia.edu I am a Distinguished Postdoctoral Fellow at the Department of Statistics at Columbia University. I received |
Keywords | N/A |
WebSite | eren-kizildag.com |
Host IP | 185.199.108.153 |
Location | - |
Site | Rank |
US$1,124
Last updated: 2023-05-20 07:14:36
eren-kizildag.com has Semrush global rank of 0. eren-kizildag.com has an estimated worth of US$ 1,124, based on its estimated Ads revenue. eren-kizildag.com receives approximately 129 unique visitors each day. Its web server is located in -, with IP address 185.199.108.153. According to SiteAdvisor, eren-kizildag.com is safe to visit. |
Purchase/Sale Value | US$1,124 |
Daily Ads Revenue | US$1 |
Monthly Ads Revenue | US$31 |
Yearly Ads Revenue | US$373 |
Daily Unique Visitors | 8 |
Note: All traffic and earnings values are estimates. |
Host | Type | TTL | Data |
eren-kizildag.com. | A | 3600 | IP: 185.199.108.153 |
eren-kizildag.com. | A | 3600 | IP: 185.199.111.153 |
eren-kizildag.com. | A | 3600 | IP: 185.199.109.153 |
eren-kizildag.com. | A | 3600 | IP: 185.199.110.153 |
eren-kizildag.com. | NS | 21600 | NS Record: ns-cloud-c3.googledomains.com. |
eren-kizildag.com. | NS | 21600 | NS Record: ns-cloud-c2.googledomains.com. |
eren-kizildag.com. | NS | 21600 | NS Record: ns-cloud-c1.googledomains.com. |
eren-kizildag.com. | NS | 21600 | NS Record: ns-cloud-c4.googledomains.com. |
Eren C. Kızıldağ e-mail : eck2170@columbia.edu I am a Distinguished Postdoctoral Fellow at the Department of Statistics at Columbia University. I received my PhD in Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT) , where I was very fortunate to be advised by Prof. David Gamarnik . At MIT, I was affiliated with the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS) . You can find my CV here. Research Interests My research revolves around problems in high-dimensional statistics , theory of machine learning , and applied probability with an emphasis on computational aspects. In particular, I would like to understand the fundamental computational limits of such problems by studying the regimes of apparent hardness where efficient algorithms cease to exist. This is often guided by the insights provided by statistical physics and spin glass theory. News April 2022 : I presented |
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