362 research outputs found
An Efficient HPR Algorithm for the Wasserstein Barycenter Problem with Computational Complexity
In this paper, we propose and analyze an efficient Halpern-Peaceman-Rachford
(HPR) algorithm for solving the Wasserstein barycenter problem (WBP) with fixed
supports. While the Peaceman-Rachford (PR) splitting method itself may not be
convergent for solving the WBP, the HPR algorithm can achieve an
non-ergodic iteration complexity with respect to the
Karush-Kuhn-Tucker (KKT) residual. More interestingly, we propose an efficient
procedure with linear time computational complexity to solve the linear systems
involved in the subproblems of the HPR algorithm. As a consequence, the HPR
algorithm enjoys an non-ergodic computational
complexity in terms of flops for obtaining an -optimal solution
measured by the KKT residual for the WBP, where is the dimension
of the variable of the WBP. This is better than the best-known complexity bound
for the WBP. Moreover, the extensive numerical results on both the synthetic
and real data sets demonstrate the superior performance of the HPR algorithm
for solving the large-scale WBP
Real-Time Bidding by Reinforcement Learning in Display Advertising
The majority of online display ads are served through real-time bidding (RTB)
--- each ad display impression is auctioned off in real-time when it is just
being generated from a user visit. To place an ad automatically and optimally,
it is critical for advertisers to devise a learning algorithm to cleverly bid
an ad impression in real-time. Most previous works consider the bid decision as
a static optimization problem of either treating the value of each impression
independently or setting a bid price to each segment of ad volume. However, the
bidding for a given ad campaign would repeatedly happen during its life span
before the budget runs out. As such, each bid is strategically correlated by
the constrained budget and the overall effectiveness of the campaign (e.g., the
rewards from generated clicks), which is only observed after the campaign has
completed. Thus, it is of great interest to devise an optimal bidding strategy
sequentially so that the campaign budget can be dynamically allocated across
all the available impressions on the basis of both the immediate and future
rewards. In this paper, we formulate the bid decision process as a
reinforcement learning problem, where the state space is represented by the
auction information and the campaign's real-time parameters, while an action is
the bid price to set. By modeling the state transition via auction competition,
we build a Markov Decision Process framework for learning the optimal bidding
policy to optimize the advertising performance in the dynamic real-time bidding
environment. Furthermore, the scalability problem from the large real-world
auction volume and campaign budget is well handled by state value approximation
using neural networks.Comment: WSDM 201
The relationship between organizational commitment and turnover intention among temporary employees in the local government: Mediating role of perceived insider status and moderating role of gender
PurposeThe purpose of this study is to examine the relationships between organizational commitment and turnover intention, and to test the mediating effect of perceived insider status, and moderating effect of gender on that relationship.MethodologyData were collected using a questionnaire survey method from 820 temporary employees of government agencies working in China. The data obtained were analyzed according to the moderated mediation.FindingsAs a result of the analysis, it was determined that perceived insider status has a partial mediation effect on the relationship between organizational commitment and turnover intention. Also, the results supported the moderated mediation and showed that the indirect effect of organizational commitment and turnover intention through perceived insider status was weaker for males than females. Then, the theoretical and practical implications of the findings are discussed
Treatment responses in adult depressive patients treated with dexamethasone/corticotrophin-releasing hormone
Purpose: To study the dexamethasone/corticotrophin releasing hormones (DEX/CRH) in depressed and healthy patients and to analyse the occurrence of relapse connected to hormonal dysregulation.Methods: A total of 117 depressive patients between 20 and 70 years of age were included in the study group and 40 healthy patients between 25 and 60 years of age in the control group. Group I consisted of 59 patients who received sertraline 50 - 100 mg/day for 5 weeks along with a low dose of 30 mg T3. Group II included 58 patients who received dexamethasone 1 mg orally for 5 weeks. DEX/CRH levels were analyzed. Adrenocorticotrophic hormone and cortisol levels in the blood were analysed by immuno-radiometric assay. Cortisol levels were also analysed by kinetic assay method.Results: In group I, among the 59 patients that received sertraline 50-100 mg/day for 5 weeks with a low dose of 30 mg T3, relapse was observed in 12 (20.3 %) of them. The area under the curve (AUC) was 13.9 ± 6.4 ng.min.1000/mL, which was higher than that for healthy individuals (3.8 ± 3.6 ng.min.1000/mL). Group I patients with relapse showed an adrenocorticotrophic hormone AUC of 16.9 ± 2.4 ng.min.1000/mL, while group II patients exhibited AUC of 13.9 ± 6.4 ng.min.1000/mL.Conclusion: The results emphasizes the need to test hormonal responses to different types of antidepressants.Keywords: stress, depressive patients, hormonal response, hormonal dysregulation, sertraline, dexamethasone, corticotrophin releasing hormon
Data Acquisition and Control System for Broad-band Microwave Reflectometry on EAST
Microwave reflectometry is a non-intrusive plasma diagnostic tool which is
widely applied in many fusion devices. In 2014, the microwave reflectometry on
Experimental Advanced Superconducting Tokamak (EAST) had been upgraded to
measure plasma density profile and fluctuation, which covered the frequency
range of Q-band (32-56 GHz), V-band (47-76 GHz) and W-band (71-110 GHz). This
paper presented a dedicated data acquisition and control system (DAQC) to meet
the measurement requirements of high accuracy and temporal resolution. The DAQC
consisted of two control modules, which integrated arbitrary waveform
generation block (AWG) and trigger processing block (TP), and two data
acquisition modules (DAQ) that was implemented base on the PXIe platform from
National Instruments (NI). All the performance parameters had satisfied the
requirements of reflectometry. The actual performance will be further examined
in the experiments of EAST in 2014.Comment: 2 pages, 2 figures, 19th IEEE-NPSS Real-Time conferenc
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