401,813 research outputs found
Non-disturbance criteria of quantum measurements
Using the general sequential product proposed by Shen and Wu in [J. Phys. A:
Math. Theor. 42, 345203, 2009], we derive three criteria for describing
non-disturbance between quantum measurements that may be unsharp with such new
sequential products, which generalizes Gudder's results
Achieving non-discrimination in prediction
Discrimination-aware classification is receiving an increasing attention in
data science fields. The pre-process methods for constructing a
discrimination-free classifier first remove discrimination from the training
data, and then learn the classifier from the cleaned data. However, they lack a
theoretical guarantee for the potential discrimination when the classifier is
deployed for prediction. In this paper, we fill this gap by mathematically
bounding the probability of the discrimination in prediction being within a
given interval in terms of the training data and classifier. We adopt the
causal model for modeling the data generation mechanism, and formally defining
discrimination in population, in a dataset, and in prediction. We obtain two
important theoretical results: (1) the discrimination in prediction can still
exist even if the discrimination in the training data is completely removed;
and (2) not all pre-process methods can ensure non-discrimination in prediction
even though they can achieve non-discrimination in the modified training data.
Based on the results, we develop a two-phase framework for constructing a
discrimination-free classifier with a theoretical guarantee. The experiments
demonstrate the theoretical results and show the effectiveness of our two-phase
framework
Faster Information Propagation on Highways: a Virtual MIMO Approach
In vehicular communications, traffic-related information should be spread
over the network as quickly as possible to maintain a safe and reliable
transportation system. This motivates us to develop more efficient information
propagation schemes. In this paper, we propose a novel cluster-based
cooperative information forwarding scheme, in which the vehicles
opportunistically form virtual antenna arrays to boost one-hop transmission
range and therefore accelerate information propagation along the highway. Both
closed-form results of the transmission range gain and the improved Information
Propagation Speed (IPS) are derived and verified by simulations. It is observed
that the proposed scheme demonstrates the most significant IPS gain in moderate
traffic scenarios, whereas too dense or too sparse vehicle density results in
less gain. Moreover, it is also shown that increased mobility offers more
contact opportunities and thus facilitates information propagation.Comment: IEEE 2014 Global Telecommunications Conference (GLOBECOM 2014) -
Communication Theory Symposiu
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