Both electron and phonon transport properties of single layer MoS2 (SLMoS2) are studied. Based on first-principles calculations, the electrical conductivity of SLMoS2 is calculated by Boltzmann equations. The thermal conductivity of SLMoS2 is calculated to be as high as 116.8 Wm−1K−1 by equilibrium molecular dynamics simulations. The predicted value of ZT is as high as 0.11 at 500 K. As the thermal conductivity could be reduced largely by phonon engineering, there should be a high possibility to enhance ZT in the SLMoS2-based materials.

It is now widely accepted that in many situations where classifiers are deployed, adversaries deliberately manipulate data in order to reduce the classifier's accuracy. The most prominent example is email spam, where spammers routinely modify emails to get past classifier-based spam filters.In this paper we model the interaction between the adversary and the data miner as a two-person sequential noncooperative Stackelberg game and analyze the outcomes when there is a natural leader and a follower. We then proceed to model the interaction (both discrete and continuous) as an optimization problem and note that even solving linear Stackelberg game is NP-Hard. Finally we use a real spam email data set and evaluate the performance of local search algorithm under different strategy spaces.

No abstract

No abstract

Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is deliberately constructed in order to increase the error rates of the classifier. A prominent example is spam email where words are transformed to get around word based features embedded in a spam filter.In this paper we model the interaction between a data miner and an adversary as a Stackelberg game with convex loss functions. We solve for the Nash equilibrium which is a pair of strategies (classifier weights, data transformations) from which there is no incentive for either the data miner or the adversary to deviate. Experiments on synthetic and real data demonstrate that the Nash equilibrium solution leads to solutions which are more robust to subsequent manipulation of data and also provide interesting insights about both the data miner and the adversary.