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Mahbod Majid on Muck Rack

Mahbod Majid

As seen in: arXiv
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Articles

Computer Science > Machine Learning

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By Tony Wu, Mahbod Majid, Ankur Moitra
| arXiv
We study the task of learning the structure of a $d$-sparse Gaussian graphical model on $n$ variables from a single trajectory of Glauber dynamics. Beyond algorithmic considerations, many applications present temporally correlated observations rather than i.i.d.\ samples. In the classical i.i.d.\ setting, under comparably general sparsity and minimum edge-strength assumptions, sublinear-in-$n$ sample guarantees are known, but achieving them in polynomial-time remains open.
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Computer Science > Cryptography and Security

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By Ephraim Linder, Mahbod Majid, Vikrant Singhal
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (693) Issue with article?

Computer Science > Data Structures and Algorithms

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By Jingqiu Ding, Mahbod Majid, Walter McKelvie
| arXiv
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