Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  addresses the problem of distributed detection in fixed and switching networks. A network of agents observe partially informative signals about the unknown state of the world. Hence, they collaborate with each other to identify the true state.  propose an update rule building on distributed, stochastic optimization methods. Our main focus is on the finite-time analysis of the problem. For fixed networks,  bring forward the notion of Kullback-Leibler cost to measure the efficiency of the algorithm versus its centralized analog.  bound the cost in terms of the network size, spectral gap and relative entropy of agents' signal structures.  further consider the problem in random networks where the structure is realized according to a stationary distribution.  then prove that the convergence is exponentially fast (with high probability), and the non-asymptotic rate scales inversely in the spectral gap of the expected network.
['Shahin Shahrampour', 'Alexander Rakhlin', 'Ali Jadbabaie']
I am writing a research paper on a idea Finite-time analysis of the distributed detection problem
[{"from": "human", "value": "I am writing a research paper on a idea Finite-time analysis of the distributed detection problem"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  addresses the problem of distributed detection in fixed and switching networks. A network of agents observe partially informative signals about the unknown state of the world. Hence, they collaborate with each other to identify the true state.  propose an update rule building on distributed, stochastic optimization methods. Our main focus is on the finite-time analysis of the problem. For fixed networks,  bring forward the notion of Kullback-Leibler cost to measure the efficiency of the algorithm versus its centralized analog.  bound the cost in terms of the network size, spectral gap and relative entropy of agents' signal structures.  further consider the problem in random networks where the structure is realized according to a stationary distribution.  then prove that the convergence is exponentially fast (with high probability), and the non-asymptotic rate scales inversely in the spectral gap of the expected network."}]