MLSP-L28.5
Time Series Anomaly Detection with Quantum Variational Methods and Set Covering
Marco Casalbore, Leonardo Lavagna, Antonello Rosato, Massimo Panella, University of Rome La Sapienza, Italy
Session:
MLSP-L28: Quantum Machine Learning Oral
Track:
Machine Learning for Signal Processing [ML]
Location:
Room 120+121
Presentation Time:
Thu, 7 May, 17:50 - 18:10
Presentation
Discussion
Resources
No resources available.
Session MLSP-L28
MLSP-L28.1: STOCHASTIC SHADOW DESCENT: TRAINING PARAMETRIZED QUANTUM CIRCUITS WITH SHADOWS OF GRADIENTS
Sayantan Pramanik, M Girish Chandra, Tata Consultancy Services, India
MLSP-L28.2: VQEzy: AN OPEN-SOURCE DATASET FOR PARAMETER INITIALIZATION IN VARIATIONAL QUANTUM EIGENSOLVERS
Chi Zhang, Indiana University, United States of America; Mengxin Zheng, Qian Lou, University of Central Florida, United States of America; Hui Min Leung, Fan Chen, Indiana University, United States of America
MLSP-L28.3: Pre-training Tensor-Train Networks Facilitates Machine Learning with Variational Quantum Circuits
Jun Qi, Georgia Institute of Technology, United States of America; Chao-Han Huck Yang, NVIDIA Research, United States of America; Pin-Yu Chen, IBM Research, United States of America; Min-Hsiu Hsieh, Hon Hai (Foxconn) Quantum Computing Research Center, Taiwan
MLSP-L28.4: Readout-Side Bypass for Residual Hybrid Quantum-Classical Models
Guilin Zhang, Wulan Guo, Ziqi Tan, George Washington University, United States of America; Hongyang He, University of Warwick, United Kingdom of Great Britain and Northern Ireland; Qiang Guan, Kent State University, United Kingdom of Great Britain and Northern Ireland; Hailong Jiang, Youngstown State University, United States of America
MLSP-L28.5: Time Series Anomaly Detection with Quantum Variational Methods and Set Covering
Marco Casalbore, Leonardo Lavagna, Antonello Rosato, Massimo Panella, University of Rome La Sapienza, Italy
MLSP-L28.6: Quantum Adaptive Self-Attention for Financial Rebalancing: An Empirical Study on Automated Market Makers in Decentralized Finance
Chi-Sheng Chen, Aidan Hung-Wen Tsai, Omnis Labs, United States of America
Contacts