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Anthony Man-Cho So

Researcher at The Chinese University of Hong Kong

Publications -  203
Citations -  8363

Anthony Man-Cho So is an academic researcher from The Chinese University of Hong Kong. The author has contributed to research in topics: Optimization problem & Computer science. The author has an hindex of 33, co-authored 173 publications receiving 6683 citations. Previous affiliations of Anthony Man-Cho So include Stanford University & Princeton University.

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Semidefinite Relaxation of Quadratic Optimization Problems

TL;DR: This article has provided general, comprehensive coverage of the SDR technique, from its practical deployments and scope of applicability to key theoretical results, and showcased several representative applications, namely MIMO detection, B¿ shimming in MRI, and sensor network localization.
Journal ArticleDOI

Outage Constrained Robust Transmit Optimization for Multiuser MISO Downlinks: Tractable Approximations by Conic Optimization

TL;DR: This paper studies a probabilistically robust transmit optimization problem under imperfect channel state information at the transmitter and under the multiuser multiple-input single-output (MISO) downlink scenario, and develops two novel approximation methods using probabilistic techniques.
Proceedings ArticleDOI

Theory of semidefinite programming for sensor network localization

TL;DR: It is shown, for the first time, that these networks can be localized in polynomial time and a notion called strong localizability is introduced and shown that the SDP model will identify all strongly localizable sub-networks in the input network.
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Outage Constrained Robust Transmit Optimization for Multiuser MISO Downlinks: Tractable Approximations by Conic Optimization

TL;DR: In this paper, a probabilistic signal-to-interference and noise ratio (SINR) constrained problem for transmit beamforming design in the presence of imperfect channel state information (CSI), under a multiuser multiple-input single-output (MISO) downlink scenario is considered.
Journal ArticleDOI

Theory of semidefinite programming for Sensor Network Localization

TL;DR: In this paper, a semidefinite programming (SDP) based model and method for the position estimation problem in sensor network localization and other Euclidean distance geometry applications is presented.