Quantum kernel methods are usually believed to enjoy better trainability than quantum neural networks which may suffer from a well-studied barren plateau. Here, building over previous evidence, the authors show that practical implications of exponential concentration result in a trivial data-insensitive model after training, and identify commonly used features that induce the concentration.
- Supanut Thanasilp
- Samson Wang
- Zoë Holmes
