Conference Information

MLCCIM 2026: International Conference on Machine Learning, Cloud Computing and Intelligent Mining

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Submission Date:
2026-06-28 Extended
Notification Date:
Conference Date:
2026-07-09
Location:
Yili, China
Years:
5
Viewed: 15678   Tracked: 0   Attend: 3

Conference Partner Index (CP-I)

44.4 / 100
Ranked #3,059 of 5,687 conferences · Top 54%

#237 of 341 in Systems & Architecture #349 of 741 in Artificial Intelligence & Machine Learning

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
48
Community attention (10%)
20
Public record completeness (15%)
35

Inputs used: Editions on record: 5 · Researchers who opened this page in the past 24 months: 14

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-27

Call For Papers

MLCCIM 2026 (International Conference on Machine Learning, Cloud Computing and Intelligent Mining) is an academic conference held in Yili, China on 2026-07-09. The paper submission deadline is 2026-06-28 (extended).

You are welcomed to submit your papers through the MLCCIM 2026 conference on topics which include: Machine Learning and Control Systems Methods, Efficiency of Reinforcement Learning Learning Enhanced Perception for Robotics Learning Enhanced Robot Planning Learning Enhanced Robot Manipulation Learning Enhanced Robot Control Handwriting Recognition Image Preprocessing and Segmentation Visual Machine Learning Techniques Reinforcement Learning for Multi-robot Cooperation or Confrontation Bionic and Medical Robots Machine learning in autonomous driving Drones and USVs Drones and Reinforcement Learning Deep Learning, Imitation Learning and Reinforcement Learning for Robotic Systems Control and Supervised Systems Machine Learning in Control Applications Telerobotics and Teleoperation Industrial Networking and Automation Networked Robots Decision Support Systems Distributed Control Systems Neural Network Based Control Systems Learning and Adaptive Control Systems Mobile Robots and Intelligent Autonomous Systems Cloud Computing and Intelligent Mining Cloud and Grid Computing for Big Data Cloud Computing Architecture and Intelligent Systems Cloud Computing Technologies, Services and Applications Cloud Optimization and Automation Infrastructure and Platforms for Intelligent Computing Data Mining Algorithms Visual Mining and Data Visualization Graph Mining Neural Network-based Data Mining Big Data Mining Based on Artificial Intelligence
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