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Ziming Zhang, Venkatesh Saligrama.  2016.  Zero-Shot Recognition via Structured Prediction. Computer Vision - {ECCV} 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part {VII}. 9911:533–548.
Ziming Zhang, Venkatesh Saligrama.  2015.  Zero-Shot Learning via Semantic Similarity Embedding. 2015 {IEEE} International Conference on Computer Vision, {ICCV} 2015, Santiago, Chile, December 7-13, 2015. :4166–4174.
Ziming Zhang, Venkatesh Saligrama.  2016.  Zero-Shot Learning via Joint Latent Similarity Embedding. 2016 {IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR} 2016, Las Vegas, NV, USA, June 27-30, 2016. :6034–6042.
Esha Ghosh, Olga Ohrimenko, Dimitrios Papadopoulos, Roberto Tamassia, Nikos Triandopoulos.  2016.  Zero-Knowledge Accumulators and Set Algebra. Advances in Cryptology - {ASIACRYPT} 2016 - 22nd International Conference on the Theory and Application of Cryptology and Information Security, Hanoi, Vietnam, December 4-8, 2016, Proceedings, Part {II}. 10032:67–100.
C. Nowzari, J. Cortes.  2014.  Zeno-free, distributed event-triggered communication and control for multi-agent average consensus. :2148-2153.

This paper studies a distributed event-triggered communication and control strategy that solves the multi-agent average consensus problem. The proposed strategy does not rely on the continuous or periodic availability of information to an agent about the state of its neighbors, but instead prescribes isolated event times where both communication and controller updates occur. In addition, all parameters required for its implementation can be locally determined by the agents. We show that the resulting network executions are guaranteed to converge to the average of the initial agents' states, establish that events cannot be triggered an infinite number of times in any finite time period (i.e., absence of Zeno behavior), and characterize the exponential rate of convergence. We also provide sufficient conditions for convergence in scenarios with time-varying communication topologies. Simulations illustrate our results.