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Quantum-inspired NN for IR Dimitris Benyou Yousef

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Page 1: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Quantum-inspired NN for IRDimitris

Benyou

Yousef

Page 2: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Why need inspiration outside CS

Energy funtion Vs Boltzmann Machine

Page 3: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Why need inspiration outside CS

local receptive field Vs CNN/Attention

Page 4: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Quantum-inspired NN

• Examples• Deep complex Network [ICLR 2018]

• LSTM + (weak value/two-state vector formulation) [ICONOP 2017]

• CNN + (wave function + superpostion collapse) [ICBI 2016]

• QLM for QA [AAAI 2018]

Page 5: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Examples: Complex Network [ICLR 2018]

Complex numberComplex convolution

Complex-valued activations

Complex weight initialization

Page 6: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Examples: LSTM with Quantum Attention[ICONIP 2017]

weak value as attention weight

Page 7: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Examples: QCNN [ICBI 2017]

Page 8: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Examples: QLM in NN [AAAI 2018]

Page 9: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

NN in IR

Page 10: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Potencial

• Representation of information• complex word embedding

• Matching Process• Quantum Neural Matching with Interference

• Translation • Sequential modelling with Quantum Mechanism

• Translation with Entanglement

Page 11: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

Schedule

Page 12: Quantum-inspired NN for IR - Benyou Wang · Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58 ... M., Shah,

References

• hen, G., Liu, Y., Cao, J., Zhong, S., Liu, Y., Hou, Y., & Zhang, P. (2017, November). Learning Music Emotions via Quantum Convolutional Neural Network. In International Conference on Brain Informatics (pp. 49-58). Springer, Cham.

• Trabelsi, C., Bilaniuk, O., Serdyuk, D., Subramanian, S., Santos, J. F., Mehri, S., ... & Pal, C. J. (2017). Deep complex networks. ICLR 2018

• Niu, X., Hou, Y., & Wang, P. (2017, November). Bi-Directional LSTM with Quantum Attention Mechanism for Sentence Modeling. ICONIP 2017

• Zhang, P., Niu, J., Su, Z., Wang, B., Ma, L., & Song, D. (2018). End-to-End Quantum-like Language Models with Application to Question Answering. AAAI 2018

• Arjovsky, M., Shah, A., & Bengio, Y. (2016, June). Unitary evolution recurrent neural networks. In International Conference on Machine Learning (pp. 1120-1128). ICML 2016


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