%20investigates%20how%20quantum%20phenomena%20can%20be%20exploited%20in%20order%20to%20learn%20data%20in%20an%20alternative%20way%2C%20textit%7Be.g.%7D%20by%20means%20of%20a%20quantum%20computer.%20While%20recent%20results%20evidence%20that%20QML%20models%20can%20potentially%20surpass%20their%20classical%20counterparts'%20performance%20in%20specific%20tasks%2C%20quantum%20technology%20hardware%20is%20still%20unready%20to%20reach%20quantum%20advantage%20in%20tasks%20of%20significant%20relevance%20to%20the%20broad%20scope%20of%20the%20computer%20science%20community.%20Recent%20advances%20indicate%20that%20hybrid%20classical-quantum%20models%20can%20readily%20attain%20competitive%20performances%20at%20low%20architecture%20complexities.%20Such%20investigations%20are%20often%20carried%20out%20for%20image-processing%20tasks%2C%20and%20are%20notably%20constrained%20to%20modelling%20textit%7Braster%20images%7D%2C%20represented%20as%20a%20grid%20of%20two-dimensional%20pixels.%20Here%2C%20we%20introduce%20vector-based%20representation%20of%20sketch%20drawings%20as%20a%20test-bed%20for%20QML%20models.%20Such%20a%20lower-dimensional%20data%20structure%20results%20handful%20to%20benchmark%20model's%20performance%2C%20particularly%20in%20current%20transition%20times%2C%20where%20classical%20simulations%20of%20quantum%20circuits%20are%20naturally%20limited%20in%20the%20number%20of%20qubits%2C%20and%20quantum%20hardware%20is%20not%20readily%20available%20to%20perform%20large-scale%20experiments.%20We%20report%20some%20encouraging%20results%20for%20primitive%20hybrid%20classical-quantum%20architectures%2C%20in%20a%20canonical%20sketch%20recognition%20problem.)
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