709 research outputs found
Memory-Efficient Topic Modeling
As one of the simplest probabilistic topic modeling techniques, latent
Dirichlet allocation (LDA) has found many important applications in text
mining, computer vision and computational biology. Recent training algorithms
for LDA can be interpreted within a unified message passing framework. However,
message passing requires storing previous messages with a large amount of
memory space, increasing linearly with the number of documents or the number of
topics. Therefore, the high memory usage is often a major problem for topic
modeling of massive corpora containing a large number of topics. To reduce the
space complexity, we propose a novel algorithm without storing previous
messages for training LDA: tiny belief propagation (TBP). The basic idea of TBP
relates the message passing algorithms with the non-negative matrix
factorization (NMF) algorithms, which absorb the message updating into the
message passing process, and thus avoid storing previous messages. Experimental
results on four large data sets confirm that TBP performs comparably well or
even better than current state-of-the-art training algorithms for LDA but with
a much less memory consumption. TBP can do topic modeling when massive corpora
cannot fit in the computer memory, for example, extracting thematic topics from
7 GB PUBMED corpora on a common desktop computer with 2GB memory.Comment: 20 pages, 7 figure
A New Approach to Speeding Up Topic Modeling
Latent Dirichlet allocation (LDA) is a widely-used probabilistic topic
modeling paradigm, and recently finds many applications in computer vision and
computational biology. In this paper, we propose a fast and accurate batch
algorithm, active belief propagation (ABP), for training LDA. Usually batch LDA
algorithms require repeated scanning of the entire corpus and searching the
complete topic space. To process massive corpora having a large number of
topics, the training iteration of batch LDA algorithms is often inefficient and
time-consuming. To accelerate the training speed, ABP actively scans the subset
of corpus and searches the subset of topic space for topic modeling, therefore
saves enormous training time in each iteration. To ensure accuracy, ABP selects
only those documents and topics that contribute to the largest residuals within
the residual belief propagation (RBP) framework. On four real-world corpora,
ABP performs around to times faster than state-of-the-art batch LDA
algorithms with a comparable topic modeling accuracy.Comment: 14 pages, 12 figure
Revisiting van der Waals like behavior of f(R) AdS black holes via the two point correlation function
Van der Waals like behavior of AdS black holes is revisited via two
point correlation function, which is dual to the geodesic length in the bulk.
The equation of motion constrained by the boundary condition is solved
numerically and both the effect of boundary region size and gravity are
probed. Moreover, an analogous specific heat related to is
introduced. It is shown that the graphs of AdS black holes
exhibit reverse van der Waals like behavior just as the graphs do. Free
energy analysis is carried out to determine the first order phase transition
temperature and the unstable branch in curve is removed by a
bar . It is shown that the first order phase transition temperature is
the same at least to the order of for different choices of the
parameter although the values of free energy vary with . Our result
further supports the former finding that charged AdS black holes behave
much like RN-AdS black holes. We also check the analogous equal area law
numerically and find that the relative errors for both the cases
and are small enough. The fitting functions between and for both cases are also
obtained. It is shown that the slope is around 3, implying that the critical
exponent is about . This result is in accordance with those in former
literatures of specific heat related to the thermal entropy or entanglement
entropy.Comment: Revised version. Match the published version. 14pages,5figure
Possible Molecular Structure of the Newly Observed Y(4260)
We suggest that the newly observed resonance Y(4260) is a
molecule, which is an isovector. In this picture, we can easily interpret why
has a larger rate than which
has not been observed, and we also predict existence of the other two
components of the isotriplet and another two possible partner states which may
be observed in the future experiments. A direct consequence of this structure
is that for this molecular structure mode is more
favorable than which may have a larger fraction if
other proposed structures prevail.Comment: 5 pages, 2 figures. Some descriptions changed, more references added
and typos corrected. Published version in PR
Deterministic and Efficient Quantum Cryptography Based on Bell's Theorem
We propose a novel double-entanglement-based quantum cryptography protocol
that is both efficient and deterministic. The proposal uses photon pairs with
entanglement both in polarization and in time degrees of freedom; each
measurement in which both of the two communicating parties register a photon
can establish one and only one perfect correlation and thus deterministically
create a key bit. Eavesdropping can be detected by violation of local realism.
A variation of the protocol shows a higher security, similarly to the six-state
protocol, under individual attacks. Our scheme allows a robust implementation
under current technology.Comment: 4 pages, 1 figure; published version with a note adde
Design and analysis of driving motor system for hybrid electric vehicle
In order to improve the reliability and stability of hybrid electric vehicle driving motor system, according to the performance parameters of the hybrid electric vehicle, the driving motor system is designed and analyzed for the hybrid electric vehicle. Based on the performance parameters of the hybrid electric vehicle, the power parameters of the permanent magnet synchronous motor (PMSM) are calculated and determined, then the parameters of the stator core, the permanent magnet and the rotor core are designed and calculated, as well as other main characteristic parameters of the driving motor system are calculated. The model of a PMSM is established and simulated by ANSOFT Maxwell according to the obtained motor parameters, and then the steady state and transient state of the driving motor are simulated in different working points, and the electromagnetic and performance curves are combined to determine the overall performance requirements of the driving motor, which can be used to match the hybrid electric vehicle. The simulation results show that the designed PMSM can be used to match the hybrid electric vehicle and meet the performance requirements of the vehicle. The final simulation analysis results are in good agreement with the theoretical calculation results, which indicates that this method can be used to afford a theoretical basis to reduce the cogging torque and optimize the in-wheel motor of electric vehicle in the future
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