BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Quantum Machine Learning
DTSTART:20260609T110000Z
DTEND:20260609T123000Z
DTSTAMP:20260811T013800Z
UID:indico-event-2120@indico.ph.liv.ac.uk
CONTACT:paolo.beltrame@liverpool.ac.uk\;M.L.Wong@liverpool.ac.uk
DESCRIPTION:Speakers: Hsi-Sheng Goan (Center for Quantum Science and Engin
 eering National Taiwan University)\n\nQuantum computing and machine learni
 ng (the core of contemporary artificial intelligence) are emerging\, promi
 sing technologies that will significantly impact human life and society. I
 t is interesting to explore the interaction between quantum computing and 
 machine learning and to study how to apply the results and technologies of
  one field to solve problems in the other. We are currently in the so-call
 ed noisy intermediate scale quantum (NISQ) era. Due to the lack of quantum
  error correction\, NISQ machines suffer from errors in state preparation\
 , measurements\, and gate operations\, making them unsuitable for deep qua
 ntum circuit architectures. A hybrid quantum-classical variational approac
 h that leverages the strengths of both quantum and classical computation i
 s suited to NISQ machines. In this talk\, I will present results for some 
 machine learning tasks using hybrid variational quantum algorithms. After 
 that\, I will introduce the quantum-train (QT) framework\, a novel approac
 h that integrates quantum computing with classical machine learning algori
 thms to tackle significant challenges in data encoding\, model compression
 \, and inference hardware requirements. If time allows\, I will also discu
 ss our recent work on quantum variational activation functions and efficie
 nt hybrid quantum-classical models for time-series forecasting.\n\nhttps:/
 /indico.ph.liv.ac.uk/event/2120/
LOCATION:OLL/3-337 (Liverpool Physics)
URL:https://indico.ph.liv.ac.uk/event/2120/
END:VEVENT
END:VCALENDAR