15406

Video URL

https://simons.berkeley.edu/talks/tbd-128

Quantum Machine Learning: Prospects and Challenges

(2020). Quantum Machine Learning: Prospects and Challenges. The Simons Institute for the Theory of Computing. https://simons.berkeley.edu/talks/tbd-128

Quantum Machine Learning: Prospects and Challenges. The Simons Institute for the Theory of Computing, Feb. 25, 2020, https://simons.berkeley.edu/talks/tbd-128 

          @misc{ scivideos_15406,
            doi = {},
            url = {https://simons.berkeley.edu/talks/tbd-128},
            author = {},
            keywords = {},
            language = {en},
            title = {Quantum Machine Learning: Prospects and Challenges},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2020},
            month = {feb},
            note = {15406 see, \url{https://scivideos.org/Simons-Institute/15406}}
          }
Iordanis Kerenidis (CNRS / QC Ware)
Talk number15406
Source RepositorySimons Institute
Subject

Abstract

We will review recent work on quantum Machine Learning with a focus on longer-term quantum algorithms. We will discuss challenges and prospects for such algorithms and ways of bringing them closer to practical solutions.