24,339 research outputs found
Joint Network and Gelfand-Pinsker Coding for 3-Receiver Gaussian Broadcast Channels with Receiver Message Side Information
The problem of characterizing the capacity region for Gaussian broadcast
channels with receiver message side information appears difficult and remains
open for N >= 3 receivers. This paper proposes a joint network and
Gelfand-Pinsker coding method for 3-receiver cases. Using the method, we
establish a unified inner bound on the capacity region of 3-receiver Gaussian
broadcast channels under general message side information configuration. The
achievability proof of the inner bound uses an idea of joint interference
cancelation, where interference is canceled by using both dirty-paper coding at
the encoder and successive decoding at some of the decoders. We show that the
inner bound is larger than that achieved by state of the art coding schemes. An
outer bound is also established and shown to be tight in 46 out of all 64
possible cases.Comment: Author's final version (presented at the 2014 IEEE International
Symposium on Information Theory [ISIT 2014]
Anisotropy in Inflation with Non-minimal Coupling
We study a new anisotropic inflation model, with an inflaton field
nonminimally coupled with the gravity and a vector field. We find that the
anisotropic attractor solution exists not only in the weak curvature coupling
limit, but more interestingly in the strong curvature coupling limit as well.
We show that in the strong curvature coupling limit, the contribution from the
anisotropy is greatly suppressed.Comment: V2, 12 pages, 3 figures, numerical analysis adde
Management of e-technology in China
"e" technology is bringing about many challenges for companies, in particular for their managers. This concerns a vast range of business processes in many sectors of the economy and in nearly every country of the world. In rapidly industrializing China, companies and other organizations are actively finding their way by adapting, developing and exploiting new e-technologies. The paper's focus is the identification of the management issues in implementing e-technology in China. The paper reports on research into difficulties of establishing and operating e-business in China. In particular, it discusses management related to e-technology sharing and application. A brief review of literature is followed by the analysis of three recent case studies: an international IT services alliance, a financial services provider and an international manufacturing joint venture. All case companies are applying e-technology in China, but the role of e-technology differs in the three cases: adding a service line to the existing business processes; developing a new business process; and increasing efficiency and effectiveness in business processes. The conclusions present the emerging management issues: cooperation is a key asset in networking; the choice of business models plays an important role; adequate management attention for details such as a training program is require
Semantics-Aligned Representation Learning for Person Re-identification
Person re-identification (reID) aims to match person images to retrieve the
ones with the same identity. This is a challenging task, as the images to be
matched are generally semantically misaligned due to the diversity of human
poses and capture viewpoints, incompleteness of the visible bodies (due to
occlusion), etc. In this paper, we propose a framework that drives the reID
network to learn semantics-aligned feature representation through delicate
supervision designs. Specifically, we build a Semantics Aligning Network (SAN)
which consists of a base network as encoder (SA-Enc) for re-ID, and a decoder
(SA-Dec) for reconstructing/regressing the densely semantics aligned full
texture image. We jointly train the SAN under the supervisions of person
re-identification and aligned texture generation. Moreover, at the decoder,
besides the reconstruction loss, we add Triplet ReID constraints over the
feature maps as the perceptual losses. The decoder is discarded in the
inference and thus our scheme is computationally efficient. Ablation studies
demonstrate the effectiveness of our design. We achieve the state-of-the-art
performances on the benchmark datasets CUHK03, Market1501, MSMT17, and the
partial person reID dataset Partial REID. Code for our proposed method is
available at:
https://github.com/microsoft/Semantics-Aligned-Representation-Learning-for-Person-Re-identification.Comment: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20),
code has been release
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