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- W3120769427 abstract "Quantifying how far the output of a learning algorithm is from its target is an essential task in machine learning. However, in quantum settings, the loss landscapes of commonly used distance metrics often produce undesirable outcomes such as poor local minima and exponentially decaying gradients. As a new approach, we consider here the quantum earth mover's (EM) or Wasserstein-1 distance, recently proposed in [De Palma et al., arXiv:2009.04469] as a quantum analog to the classical EM distance. We show that the quantum EM distance possesses unique properties, not found in other commonly used quantum distance metrics, that make quantum learning more stable and efficient. We propose a quantum Wasserstein generative adversarial network (qWGAN) which takes advantage of the quantum EM distance and provides an efficient means of performing learning on quantum data. Our qWGAN requires resources polynomial in the number of qubits, and our numerical experiments demonstrate that it is capable of learning a diverse set of quantum data." @default.
- W3120769427 created "2021-01-18" @default.
- W3120769427 creator A5007373481 @default.
- W3120769427 creator A5038060570 @default.
- W3120769427 creator A5055460463 @default.
- W3120769427 creator A5061177049 @default.
- W3120769427 creator A5079855181 @default.
- W3120769427 date "2021-01-08" @default.
- W3120769427 modified "2023-09-26" @default.
- W3120769427 title "Quantum Earth Mover's Distance: A New Approach to Learning Quantum Data" @default.
- W3120769427 cites W1522301498 @default.
- W3120769427 cites W1522579744 @default.
- W3120769427 cites W1568345435 @default.
- W3120769427 cites W1574861711 @default.
- W3120769427 cites W1631356911 @default.
- W3120769427 cites W1983672937 @default.
- W3120769427 cites W1990514347 @default.
- W3120769427 cites W2030545386 @default.
- W3120769427 cites W2041951427 @default.
- W3120769427 cites W2051625847 @default.
- W3120769427 cites W2065171116 @default.
- W3120769427 cites W2092066661 @default.
- W3120769427 cites W2099471712 @default.
- W3120769427 cites W2101575317 @default.
- W3120769427 cites W2125101937 @default.
- W3120769427 cites W2158230813 @default.
- W3120769427 cites W2405098100 @default.
- W3120769427 cites W2468412683 @default.
- W3120769427 cites W2523862792 @default.
- W3120769427 cites W2581719241 @default.
- W3120769427 cites W2617573776 @default.
- W3120769427 cites W2618530766 @default.
- W3120769427 cites W2703190149 @default.
- W3120769427 cites W2734648283 @default.
- W3120769427 cites W2752849906 @default.
- W3120769427 cites W2755255888 @default.
- W3120769427 cites W2759973161 @default.
- W3120769427 cites W2766527293 @default.
- W3120769427 cites W2767328092 @default.
- W3120769427 cites W2768206303 @default.
- W3120769427 cites W2775342956 @default.
- W3120769427 cites W2781132081 @default.
- W3120769427 cites W2785678896 @default.
- W3120769427 cites W2790388700 @default.
- W3120769427 cites W2791361942 @default.
- W3120769427 cites W2796293949 @default.
- W3120769427 cites W2797767079 @default.
- W3120769427 cites W2798945316 @default.
- W3120769427 cites W2798967590 @default.
- W3120769427 cites W2799565130 @default.
- W3120769427 cites W2803978172 @default.
- W3120769427 cites W2804078698 @default.
- W3120769427 cites W2808711456 @default.
- W3120769427 cites W2891641674 @default.
- W3120769427 cites W2898620356 @default.
- W3120769427 cites W2900328136 @default.
- W3120769427 cites W2901859177 @default.
- W3120769427 cites W2903221501 @default.
- W3120769427 cites W2903712458 @default.
- W3120769427 cites W2907827190 @default.
- W3120769427 cites W2908171520 @default.
- W3120769427 cites W2949863591 @default.
- W3120769427 cites W2962691920 @default.
- W3120769427 cites W2962730419 @default.
- W3120769427 cites W2962767882 @default.
- W3120769427 cites W2962879692 @default.
- W3120769427 cites W2962949934 @default.
- W3120769427 cites W2963061092 @default.
- W3120769427 cites W2963187803 @default.
- W3120769427 cites W2963341956 @default.
- W3120769427 cites W2963403868 @default.
- W3120769427 cites W2963444790 @default.
- W3120769427 cites W2963656694 @default.
- W3120769427 cites W2963784808 @default.
- W3120769427 cites W2964155450 @default.
- W3120769427 cites W2970821532 @default.
- W3120769427 cites W2970971581 @default.
- W3120769427 cites W2971455341 @default.
- W3120769427 cites W2989335074 @default.
- W3120769427 cites W2989564043 @default.
- W3120769427 cites W2990288734 @default.
- W3120769427 cites W2997552416 @default.
- W3120769427 cites W3000145673 @default.
- W3120769427 cites W3000624483 @default.
- W3120769427 cites W3004252283 @default.
- W3120769427 cites W3004326598 @default.
- W3120769427 cites W3009330671 @default.
- W3120769427 cites W3009495986 @default.
- W3120769427 cites W3014599029 @default.
- W3120769427 cites W3029180882 @default.
- W3120769427 cites W3030163527 @default.
- W3120769427 cites W3030829226 @default.
- W3120769427 cites W3032784257 @default.
- W3120769427 cites W3033233627 @default.
- W3120769427 cites W3039256091 @default.
- W3120769427 cites W3043339303 @default.
- W3120769427 cites W3045606049 @default.
- W3120769427 cites W3047824577 @default.
- W3120769427 cites W3088590922 @default.
- W3120769427 cites W3094555598 @default.