International Conference on Machine Learning (ICML) Vancouver 2025

Name: International Conference on Machine Learning (ICML) Vancouver 2025
Start: 2025-07-13T09:00:00-07:00
End: 2025-07-19T17:00:00-07:00

Conference

Date

Jul 13, 2025 –

Sunday

Jul 19, 2025

Saturday

Time

9:00 AM – 5:00 PM

(UTC-07:00) Pacific Time (Los Angeles)

Location

Vancouver, Canada

What You’ll Learn

The Forty-Second International Conference on Machine Learning (ICML) is scheduled from July 13 to July 19, 2025, at the Vancouver Convention Center in Vancouver, British Columbia, Canada. This conference is a leading forum for professionals dedicated to the advancement of machine learning.

ICML 2025 will feature tutorials on July 14, main conference sessions from July 15 to 17, and workshops on July 18 and 19. The event will also include an expo on July 13, providing a platform for industry and academic professionals to present and discuss the latest developments in machine learning.

ICML 2025 Event Themes

General Machine Learning: Topics such as active learning, clustering, online learning, and time series analysis, relevant for researchers and practitioners in various sectors.
Deep Learning: Discussions on architectures, generative models, and theoretical advancements, beneficial for professionals developing AI systems.
Evaluation: Methodologies, meta-studies, replicability, and human-in-the-loop processes, essential for ensuring the reliability of machine learning models.
Theory of Machine Learning: Statistical learning theory, bandits, game theory, and decision theory, providing foundational knowledge for academic researchers.
Machine Learning Systems: Implementation scalability, hardware considerations, libraries, and distributed methods, crucial for system architects and engineers.
Optimization: Techniques in convex and non-convex optimization, matrix/tensor methods, and stochastic processes, important for algorithm developers.
Probabilistic Methods: Bayesian methods, graphical models, and Monte Carlo methods, applicable to data scientists and statisticians.
Reinforcement Learning: Decision and control, planning, hierarchical RL, and robotics, relevant for professionals in automation and robotics.
Trustworthy Machine Learning: Causality, fairness, interpretability, privacy, robustness, and safety, critical for compliance officers and ethicists.
Application-Driven Machine Learning: Innovative techniques and datasets in healthcare, physical sciences, biosciences, social sciences, sustainability, and climate, targeting applied machine learning professionals.

ICML 2025 Target Audience

Academic and industrial researchers in machine learning
Data scientists and statisticians
Software engineers and system architects
Graduate students and postdoctoral researchers

ICML 2025 Offerings

Conference Sessions: Presentations and discussions on the latest research and developments in machine learning.
Tutorials: In-depth sessions on core and emerging machine learning topics, scheduled for July 14.
Workshops: Collaborative sessions focusing on specific areas within machine learning, held on July 18 and 19.
Expo: An exhibition space for sponsors and exhibitors to showcase their products and services, taking place on July 13.
Networking Opportunities: Events and platforms facilitating interaction among attendees from academia and industry.