In various embodiments, a predictive assignment application computes a forecasted amount of processor use for each workload included in a set of workloads using a trained machine-learning model. Based on the forecasted amounts of processor use, the predictive assignment application computes a performance cost estimate associated with an estimated level of cache interference arising from executing the set of workloads on a set of processors. Subsequently, the predictive assignment application determines processor assignment(s) based on the performance cost estimate. At least one processor included in the set of processors is subsequently configured to execute at least a portion of a first workload that is included in the set of workloads based on the processor assignment(s). Advantageously, because the predictive assignment application generates the processor assignment(s) based on the forecasted amounts of processor use, the isolation application can reduce interference in a non-uniform memory access (NUMA) microprocessor instance.