A method for a network-optimization controller of a core network, the method comprising the network-optimization controller: determining a performance metric to optimize for a cellular network; determining at least one network-configuration parameter that affects the performance metric; sending a gradient-request message to multiple base stations that directs multiple wireless transceivers to respectively evaluate gradients of the performance metric relative to the at least one network-configuration parameter, the at least one network-configuration parameter specifying respective operational configurations of the multiple wireless transceivers, the multiple wireless transceivers including a user equipment and at least one other user equipment or base station of the multiple base stations, the at least one user equipment in communication with at least one of the multiple base stations; receiving, from the multiple base stations, gradient-report messages generated by the multiple wireless transceivers, the gradient-report messages respectively including the gradients, the gradients specifying an amount of change in the performance metric relative to an amount of change in the at least one network-configuration parameter; determining at least one optimized network-configuration parameter by analyzing the gradients using machine learning, the at least one optimized network-configuration parameter associated with a local optima or global optima of a function associated with the performance metric; and sending an optimization message to at least one of the multiple base stations that directs at least one of the multiple wireless transceivers to use the at least one optimized network-configuration parameter. determining a performance metric to optimize for a cellular network; determining at least one network-configuration parameter that affects the performance metric; sending a gradient-request message to multiple base stations that directs multiple wireless transceivers to respectively evaluate gradients of the performance metric relative to the at least one network-configuration parameter, the at least one network-configuration parameter specifying respective operational configurations of the multiple wireless transceivers, the multiple wireless transceivers including a user equipment and at least one other user equipment or base station of the multiple base stations, the at least one user equipment in communication with at least one of the multiple base stations; receiving, from the multiple base stations, gradient-report messages generated by the multiple wireless transceivers, the gradient-report messages respectively including the gradients, the gradients specifying an amount of change in the performance metric relative to an amount of change in the at least one network-configuration parameter; determining at least one optimized network-configuration parameter by analyzing the gradients using machine learning, the at least one optimized network-configuration parameter associated with a local optima or global optima of a function associated with the performance metric; and sending an optimization message to at least one of the multiple base stations that directs at least one of the multiple wireless transceivers to use the at least one optimized network-configuration parameter.