Junfeng Cao

Learning to Weight Samples for Dynamic Early-Exiting Networks

"Early exiting is an effective paradigm for improving the inference efficiency of deep networks. By constructing classifiers with varying resource demands (the exits), such networks allow easy samples to be output at early exits, removing the need for executing deeper layers. While existing works ma…