ICML 2026: Forty-Third International Conference on Machine Learning

COEX Convention & Exhibition Center

Jul 6 - 12, 2026

COEX Convention & Exhibition Center

Seoul, Korea (South)

Jul 6 - 12, 2026

Seoul, Korea (South)

About the Conference

The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

Subject Areas

Topics of interest include (but are not limited to)

Important Dates

2026-01-08 Paper Submission Opens for Main Conference CLOSED

2026-01-23 Abstract Submission Deadline · Jan 23, 2026 (Anywhere on Earth) CLOSED

2026-01-28 Full Paper Submission Deadline · Jan 28, 2026 (Anywhere on Earth) CLOSED

2026-03-12 Deadline for Reviews · Mar 12, 2026 (Anywhere on Earth) CLOSED

2026-03-24 Reviews Released to Authors · Mar 24, 2026 (Anywhere on Earth) CLOSED

2026-03-30 Author Response Deadline · Mar 30, 2026 (Anywhere on Earth) CLOSED

2026-04-30 Author Notification · Apr 30, 2026 (Anywhere on Earth) CLOSED

2026-05-11 In-person Presentation Questionnaire Deadline · 11:59pm AOE CLOSED

2026-05-24 Early pricing before this date · May 24, 2026 (Anywhere on Earth) CLOSED

2026-05-28 Camera-ready Submission Deadline · 11:59pm AOE CLOSED

2026-06-17 Registration Cancellation Deadline · Jun 17, 2026 (Anywhere on Earth) CLOSED

2026-07-06 Conference Dates · Tutorials/Expo Talks Mon Jul 6th; Main Conference Tue Jul 7th through Thu Jul 9th; Workshops Fri Jul 10th through Sat Jul 11th CLOSED

Call For Papers

Topics of interest include (but are not limited to)

general machine learning (active learning, clustering, online learning, ranking, supervised, semi- and self-supervised learning, time series analysis, etc.) deep learning (architectures, generative models, theory, etc.) evaluation (methodology, meta studies, replicability and validity, human-in-the-loop, etc.) theory of machine learning (statistical learning theory, bandits, game theory, decision theory, etc.) machine learning systems (improved implementation and scalability, hardware, libraries, distributed methods, etc.) optimization (convex and non-convex optimization, matrix/tensor methods, stochastic, online, non-smooth, composite, etc.) probabilistic methods (Bayesian methods, graphical models, Monte Carlo methods, etc.) reinforcement learning (decision and control, planning, hierarchical RL, robotics, etc.) trustworthy machine learning (reliability, causality, fairness, interpretability, privacy, robustness, safety, etc.) application-driven machine learning (innovative techniques, problems, and datasets that are of interest to the machine learning community and driven by the needs of end-users in applications such as healthcare, physical sciences, biosciences, social sciences, sustainability, and climate etc.)

Publication & Indexing

PublisherProceedings of Machine Learning Research (PMLR)

ProceedingsProceedings of Machine Learning Research

IndexingICML Proceedings at PMLR; papers published at ICML are indexed in the Proceedings of Machine Learning Research through the Journal of Machine Learning Research

Conference Organization

In cooperation with

IMLS

Committee

General Chair

Tong Zhang

University of Illinois

Program Chair

Miroslav Dudik

Microsoft Research

Martin Jaggi

EPFL

Alekh Agarwal

Google

Sharon Li

University of Wisconsin-Madison

Ethics Chair

Lydia T. Liu

Princeton University

Asia Biega

Max Planck

Position Paper Track Chair

Dale Schuurmans

Google DeepMind / University of Alberta

Jerry Zhu

University of Wisconsin-Madison

Scientific Integrity Chair

Nihar Shah

Carnegie Mellon University

Weijie Su

OpenAI

Katherine Heller

Google

Workshop Chair

Courtney Paquette

McGill University/Google DeepMind

Gergely Neu

Universitat Pompeu Fabra & ICREA

Tutorial Chair

Claire Vernade

University of Technology Nuremberg (UTN)

Adam White

University of Alberta, Alberta Machine Intelligence Institute (Amii), RL Core

Publication Chair

Felix Berkenkamp

Aleph Alpha Research

Hanze Dong

Microsoft

Alberto Bietti

Flatiron Institute

Associate Chair

Hyeong Kyu Choi

University of Wisconsin-Madison

Alexander Hägele

EPFL

Buxin Su

University of Pennsylvania

Communications Chair

Gautam Kamath

University of Waterloo

Katherine Gorman

Talking Machines

Tegan Emerson

Pacific Northwest National Laboratory

Social Chair

Kevin Leyton-Brown

University of British Columbia

Chulhee Yun

KAIST

Local Chairs

Chang D. Yoo

Kaist

Inclusion & Accessibility Chair

Amy Zhang

UT Austin

Maria Skoularidou

Broad Institute

Expo Chair

Ismini Lourentzou

University of Illinois Urbana-Champaign

Wenming Ye

Renice.AI

Workflow Chair

Zhenyu (Sherry) Xue

ICML

Conference Production

Lee Campbell

Eventhosts.cc

Mary Ellen Perry

Eventhosts

Brad Brockmeyer

ICML Staff

Tony Manzo

ICML Staff

Brian Nettleton

ICML Staff

Max Wiesner

ICML

Stephanie Willes

ICML Conference Staff