BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Venue Radar//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:L4DC 2027 Calendar
BEGIN:VEVENT
UID:l4dc-2027-deadline-full-paper@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART;VALUE=DATE:20261113
DTEND;VALUE=DATE:20261114
SUMMARY:[Machine Learning][Control & Robotics] L4DC 2027 - Paper submission
  deadline (cutoff time unannounced)
DESCRIPTION:Conference title: Learning for Dynamics and Control\nWebsite: h
 ttps://l4dc2027.control.ee.ethz.ch/home\nSource URL: https://l4dc2027.con
 trol.ee.ethz.ch/home\nLocation: Stockholm\, Sweden\nTopics: Machine Learn
 ing\, Control & Robotics\, System Identification & Data-driven Dynamics\,
  Reinforcement Learning\nSize: M\nSubmission type: Paper-based\nConfidenc
 e: confirmed\nLast checked date: 2026-10-06\nNotes: Annual conference at 
 the ML/control interface\, hosted by KTH. Official days are published\; c
 utoff hours are unannounced and represented using estimated end-of-day Ao
 E timing. Late-breaking results are a separate presentation route\, not r
 egular proceedings papers. Size is an editorial scale category\, not a ve
 rified attendance count.\nScope: The interface of learning\, dynamics\, c
 ontrol\, and optimization for physical and dynamical systems. Emphasizes 
 foundations and methods for data-driven control and dynamical modeling\, 
 including theoretical\, empirical\, and applied contributions. Pure patte
 rn recognition without a meaningful connection to dynamics or control is 
 not the defining focus.\nAdditional topics: Learning Theory & Statistical
  Foundations\nScope sources (2027): https://l4dc2027.control.ee.ethz.ch/h
 ome\nScope last checked: 2026-10-07\nOfficial deadline day\; exact cutoff
  hour/timezone is unannounced. Verify the organizer's submission portal.
URL:https://l4dc2027.control.ee.ethz.ch/home
END:VEVENT
BEGIN:VEVENT
UID:l4dc-2027-deadline-notification@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART;VALUE=DATE:20270125
DTEND;VALUE=DATE:20270126
SUMMARY:[Machine Learning][Control & Robotics] L4DC 2027 - Acceptance notif
 ication (cutoff time unannounced)
DESCRIPTION:Conference title: Learning for Dynamics and Control\nWebsite: h
 ttps://l4dc2027.control.ee.ethz.ch/home\nSource URL: https://l4dc2027.con
 trol.ee.ethz.ch/home\nLocation: Stockholm\, Sweden\nTopics: Machine Learn
 ing\, Control & Robotics\, System Identification & Data-driven Dynamics\,
  Reinforcement Learning\nSize: M\nSubmission type: Paper-based\nConfidenc
 e: confirmed\nLast checked date: 2026-10-06\nNotes: Annual conference at 
 the ML/control interface\, hosted by KTH. Official days are published\; c
 utoff hours are unannounced and represented using estimated end-of-day Ao
 E timing. Late-breaking results are a separate presentation route\, not r
 egular proceedings papers. Size is an editorial scale category\, not a ve
 rified attendance count.\nScope: The interface of learning\, dynamics\, c
 ontrol\, and optimization for physical and dynamical systems. Emphasizes 
 foundations and methods for data-driven control and dynamical modeling\, 
 including theoretical\, empirical\, and applied contributions. Pure patte
 rn recognition without a meaningful connection to dynamics or control is 
 not the defining focus.\nAdditional topics: Learning Theory & Statistical
  Foundations\nScope sources (2027): https://l4dc2027.control.ee.ethz.ch/h
 ome\nScope last checked: 2026-10-07\nOfficial deadline day\; exact cutoff
  hour/timezone is unannounced. Verify the organizer's submission portal.
URL:https://l4dc2027.control.ee.ethz.ch/home
END:VEVENT
BEGIN:VEVENT
UID:l4dc-2027-deadline-late-breaking@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART;VALUE=DATE:20270405
DTEND;VALUE=DATE:20270406
SUMMARY:[Machine Learning][Control & Robotics] L4DC 2027 - Late-breaking re
 sults (eligibility to be announced) (cutoff time unannounced)
DESCRIPTION:Conference title: Learning for Dynamics and Control\nWebsite: h
 ttps://l4dc2027.control.ee.ethz.ch/home\nSource URL: https://l4dc2027.con
 trol.ee.ethz.ch/home\nLocation: Stockholm\, Sweden\nTopics: Machine Learn
 ing\, Control & Robotics\, System Identification & Data-driven Dynamics\,
  Reinforcement Learning\nSize: M\nSubmission type: Paper-based\nConfidenc
 e: confirmed\nLast checked date: 2026-10-06\nNotes: Annual conference at 
 the ML/control interface\, hosted by KTH. Official days are published\; c
 utoff hours are unannounced and represented using estimated end-of-day Ao
 E timing. Late-breaking results are a separate presentation route\, not r
 egular proceedings papers. Size is an editorial scale category\, not a ve
 rified attendance count.\nScope: The interface of learning\, dynamics\, c
 ontrol\, and optimization for physical and dynamical systems. Emphasizes 
 foundations and methods for data-driven control and dynamical modeling\, 
 including theoretical\, empirical\, and applied contributions. Pure patte
 rn recognition without a meaningful connection to dynamics or control is 
 not the defining focus.\nAdditional topics: Learning Theory & Statistical
  Foundations\nScope sources (2027): https://l4dc2027.control.ee.ethz.ch/h
 ome\nScope last checked: 2026-10-07\nOfficial deadline day\; exact cutoff
  hour/timezone is unannounced. Verify the organizer's submission portal.
URL:https://l4dc2027.control.ee.ethz.ch/home
END:VEVENT
BEGIN:VEVENT
UID:l4dc-2027-deadline-camera-ready@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART;VALUE=DATE:20270419
DTEND;VALUE=DATE:20270420
SUMMARY:[Machine Learning][Control & Robotics] L4DC 2027 - Camera-ready dea
 dline (cutoff time unannounced)
DESCRIPTION:Conference title: Learning for Dynamics and Control\nWebsite: h
 ttps://l4dc2027.control.ee.ethz.ch/home\nSource URL: https://l4dc2027.con
 trol.ee.ethz.ch/home\nLocation: Stockholm\, Sweden\nTopics: Machine Learn
 ing\, Control & Robotics\, System Identification & Data-driven Dynamics\,
  Reinforcement Learning\nSize: M\nSubmission type: Paper-based\nConfidenc
 e: confirmed\nLast checked date: 2026-10-06\nNotes: Annual conference at 
 the ML/control interface\, hosted by KTH. Official days are published\; c
 utoff hours are unannounced and represented using estimated end-of-day Ao
 E timing. Late-breaking results are a separate presentation route\, not r
 egular proceedings papers. Size is an editorial scale category\, not a ve
 rified attendance count.\nScope: The interface of learning\, dynamics\, c
 ontrol\, and optimization for physical and dynamical systems. Emphasizes 
 foundations and methods for data-driven control and dynamical modeling\, 
 including theoretical\, empirical\, and applied contributions. Pure patte
 rn recognition without a meaningful connection to dynamics or control is 
 not the defining focus.\nAdditional topics: Learning Theory & Statistical
  Foundations\nScope sources (2027): https://l4dc2027.control.ee.ethz.ch/h
 ome\nScope last checked: 2026-10-07\nOfficial deadline day\; exact cutoff
  hour/timezone is unannounced. Verify the organizer's submission portal.
URL:https://l4dc2027.control.ee.ethz.ch/home
END:VEVENT
BEGIN:VEVENT
UID:l4dc-2027-conference@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART;VALUE=DATE:20270616
DTEND;VALUE=DATE:20270619
SUMMARY:[Machine Learning][Control & Robotics] L4DC 2027 - Conference
DESCRIPTION:Conference title: Learning for Dynamics and Control\nWebsite: h
 ttps://l4dc2027.control.ee.ethz.ch/home\nSource URL: https://l4dc2027.con
 trol.ee.ethz.ch/home\nLocation: Stockholm\, Sweden\nTopics: Machine Learn
 ing\, Control & Robotics\, System Identification & Data-driven Dynamics\,
  Reinforcement Learning\nSize: M\nSubmission type: Paper-based\nConfidenc
 e: confirmed\nLast checked date: 2026-10-06\nNotes: Annual conference at 
 the ML/control interface\, hosted by KTH. Official days are published\; c
 utoff hours are unannounced and represented using estimated end-of-day Ao
 E timing. Late-breaking results are a separate presentation route\, not r
 egular proceedings papers. Size is an editorial scale category\, not a ve
 rified attendance count.\nScope: The interface of learning\, dynamics\, c
 ontrol\, and optimization for physical and dynamical systems. Emphasizes 
 foundations and methods for data-driven control and dynamical modeling\, 
 including theoretical\, empirical\, and applied contributions. Pure patte
 rn recognition without a meaningful connection to dynamics or control is 
 not the defining focus.\nAdditional topics: Learning Theory & Statistical
  Foundations\nScope sources (2027): https://l4dc2027.control.ee.ethz.ch/h
 ome\nScope last checked: 2026-10-07
URL:https://l4dc2027.control.ee.ethz.ch/home
LOCATION:Stockholm\, Sweden
END:VEVENT
END:VCALENDAR