23,641 research outputs found
LATTE: Application Oriented Social Network Embedding
In recent years, many research works propose to embed the network structured
data into a low-dimensional feature space, where each node is represented as a
feature vector. However, due to the detachment of embedding process with
external tasks, the learned embedding results by most existing embedding models
can be ineffective for application tasks with specific objectives, e.g.,
community detection or information diffusion. In this paper, we propose study
the application oriented heterogeneous social network embedding problem.
Significantly different from the existing works, besides the network structure
preservation, the problem should also incorporate the objectives of external
applications in the objective function. To resolve the problem, in this paper,
we propose a novel network embedding framework, namely the "appLicAtion
orienTed neTwork Embedding" (Latte) model. In Latte, the heterogeneous network
structure can be applied to compute the node "diffusive proximity" scores,
which capture both local and global network structures. Based on these computed
scores, Latte learns the network representation feature vectors by extending
the autoencoder model model to the heterogeneous network scenario, which can
also effectively unite the objectives of network embedding and external
application tasks. Extensive experiments have been done on real-world
heterogeneous social network datasets, and the experimental results have
demonstrated the outstanding performance of Latte in learning the
representation vectors for specific application tasks.Comment: 11 Pages, 12 Figures, 1 Tabl
On Identity Tests for High Dimensional Data Using RMT
In this work, we redefined two important statistics, the CLRT test (Bai
et.al., Ann. Stat. 37 (2009) 3822-3840) and the LW test (Ledoit and Wolf, Ann.
Stat. 30 (2002) 1081-1102) on identity tests for high dimensional data using
random matrix theories. Compared with existing CLRT and LW tests, the new tests
can accommodate data which has unknown means and non-Gaussian distributions.
Simulations demonstrate that the new tests have good properties in terms of
size and power. What is more, even for Gaussian data, our new tests perform
favorably in comparison to existing tests. Finally, we find the CLRT is more
sensitive to eigenvalues less than 1 while the LW test has more advantages in
relation to detecting eigenvalues larger than 1.Comment: 16 pages, 2 figures, 3 tables, To be published in the Journal of
Multivariate Analysi
The Happer's puzzle degeneracies and Yangian
We find operators distinguishing the degenerate states for the Hamiltonian
at that was given by Happer
et al to interpret the curious degeneracies of the Zeeman effect for
condensed vapor of Rb. The operators obey Yangian commutation relations.
We show that the curious degeneracies seem to verify the Yangian algebraic
structure for quantum tensor space and are consistent with the representation
theory of .Comment: 8 pages, Latex fil
Accessible Capacity of Secondary Users
A new problem formulation is presented for the Gaussian interference channels
(GIFC) with two pairs of users, which are distinguished as primary users and
secondary users, respectively. The primary users employ a pair of encoder and
decoder that were originally designed to satisfy a given error performance
requirement under the assumption that no interference exists from other users.
In the scenario when the secondary users attempt to access the same medium, we
are interested in the maximum transmission rate (defined as {\em accessible
capacity}) at which secondary users can communicate reliably without affecting
the error performance requirement by the primary users under the constraint
that the primary encoder (not the decoder) is kept unchanged. By modeling the
primary encoder as a generalized trellis code (GTC), we are then able to treat
the secondary link and the cross link from the secondary transmitter to the
primary receiver as finite state channels (FSCs). Based on this, upper and
lower bounds on the accessible capacity are derived. The impact of the error
performance requirement by the primary users on the accessible capacity is
analyzed by using the concept of interference margin. In the case of
non-trivial interference margin, the secondary message is split into common and
private parts and then encoded by superposition coding, which delivers a lower
bound on the accessible capacity. For some special cases, these bounds can be
computed numerically by using the BCJR algorithm. Numerical results are also
provided to gain insight into the impacts of the GTC and the error performance
requirement on the accessible capacity.Comment: 42 pages, 12 figures, 2 tables; Submitted to IEEE Transactions on
Information Theory on December, 2010, Revised on November, 201
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