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IEEE International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING

25/10/2021 to 28/10/2021, Gold Coast, Queensland, Australia

The 31st MLSP workshop in the series of workshops organized by the IEEE Signal Processing Society MLSP Technical Committee will take place in Gold Coast, Australia. The conference will be held through a virtual program for all attendees. The conference will present the most recent and exciting advances in machine learning for signal processing through keynote talks, tutorials, special and regular single-track sessions as well as matchmaking events. The presented papers will be published in and indexed by IEEE Xplore.

Announcements

The papers selected by the Award Committee have been announced.
IMPORTANT: Please take note of the instructions for virtual presentations here.
Virtual presentation background images are available for download here.
Registration is now open. Rates can be found here.
Dr. Shang-Hong Lai will be presenting an industry keynote speech at MLSP 2021. More information can be found here.
MLSP 2021 will be fully virtual.
Prof. Matthew Turk will be presenting a keynote speech at MLSP 2021. More information can be found here.
Paper submission deadline has been extended to June 14th 2021.
Prof. Kristen Grauman will present a plenary talk at MLSP 2021. For more information please visit Plenaries page.
Prof. Yousef Saad will present a plenary talk at MLSP2021.
Prof. Ravi Ramamoorthi will present a plenary talk at MLSP2021.
MLSP 2023 Call for Proposals is now available.

Important Dates

  • Deadline for special session proposals submission April 30th, 2021 
  • Special sessions selected May 7th, 2021
  • Deadline for 6-page paper submissions May 31st, 2021 has been extended to June 14th, 2021
  • Notification of paper acceptance July 31st, 2021 August 31st, 2021
  • Camera ready upload August 31st, 2021 September 30th, 2021 September 13th, 2021
  • Start of conference October 25th, 2021

For more details, see the Call for Papers.

 

Data Competition: L3DAS21
Machine Learning for 3D Audio Signal Processing

Information for the 3D audio signal processing challenge can be found in the L3DAS21 Challenge Description. The challenge home-page can be found here.

 

Special Sessions
Machine Learning for 3D Audio Signal Processing

Information regarding special sessions can be found in the Call for Special Sessions.

 

Sponsors