@techreport{oai:ipsj.ixsq.nii.ac.jp:00217652,
 author = {Chih-Chieh, Chen and Masaru, Sogabe and Kodai, Shiba and Katsuyoshi, Sakamoto and Tomah, Sogabe and Chih-Chieh, Chen and Masaru, Sogabe and Kodai, Shiba and Katsuyoshi, Sakamoto and Tomah, Sogabe},
 issue = {30},
 month = {Mar},
 note = {Previously we established a VC dimension upper bound for ”encoding-first” quantum circuits, where the input layer is the first layer of the circuit. In this report, we prove a general VC dimension upper bound for quantum circuit learning including ”data re-uploading” circuits, where the input gates can be single qubit rotations anywhere in the circuit. We discuss the properties of the bound and some other considerations., Previously we established a VC dimension upper bound for ”encoding-first” quantum circuits, where the input layer is the first layer of the circuit. In this report, we prove a general VC dimension upper bound for quantum circuit learning including ”data re-uploading” circuits, where the input gates can be single qubit rotations anywhere in the circuit. We discuss the properties of the bound and some other considerations.},
 title = {A general VC dimension upper bound for quantum circuit learning},
 year = {2022}
}