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most citedDeepPose: Human Pose Estimation via Deep Neural Networks

3.3k citations

Showing 2016Show all

22 papers · 1 filter

astro-ph.GA2016★ 15 cited

A systematic observational study of radio properties of H2O megamaser Seyfert-2 galaxies

Z. W. Liu, J. S. Zhang, C. Henkel +5

A systematic study is performed on radio properties of HO megamaser host Seyfert 2 galaxies, through multi-band radio continuum observations (at 11cm, 6.0 cm, 3.6 cm, 2.0 cm…

astro-ph.GA2016★ 11 cited

Millimeter Spectral Line Mapping Observations Toward Four Massive Star Forming HII Regions

Shanghuo Li, Junzhi Wang, Zhi-Yu Zhang +6

We present spectral line mapping observations toward four massive star-forming regions (Cepheus A, DR21S, S76E and G34.26+0.15), with the IRAM 30 meter telescope at 2 mm and 3 mm b…

math.OC2016

Exact recovery low-rank matrix via transformed affine matrix rank minimization

Angang Cui, Jigen Peng, Haiyang Li

The goal of affine matrix rank minimization problem is to reconstruct a low-rank or approximately low-rank matrix under linear constraints. In general, this problem is combinatoria…

math.QA2016★ 19 cited

Finite dimensional Hopf algebras over Kac-Paljutkin algebra

Yuxing Shi

Let be the neither commutative nor cocommutative semisimple eight dimensional Hopf algebra, which is also called Kac-Paljutkin algebra \cite{MR0208401}. All simple Yetter-Dri…

astro-ph.HE2016★ 45 cited

Multiband optical variability of the blazar OJ 287 during its outbursts in 2015 -- 2016

Alok C. Gupta, A. Agarwal, A. Mishra +31

We present recent optical photometric observations of the blazar OJ 287 taken during September 2015 -- May 2016. Our intense observations of the blazar started in November 2015 and…

math.OC2016★ 1 cited

Affine matrix rank minimization problem via non-convex fraction function penalty

Angang Cui, Jigen Peng, Haiyang Li +2

Affine matrix rank minimization problem is a fundamental problem with a lot of important applications in many fields. It is well known that this problem is combinatorial and NP-har…