We consider a multi-agent framework for distributed optimization where each agent has access to local smooth strongly convex function, and the collective goal is achieve consensus on parameters that minimize sum of agents' functions. propose an algorithm wherein operates asynchronously independently other agents. When functions are strongly-convex with Lipschitz-continuous gradients, we show it...