WiML Un-Workshop 2021 @ ICML: Participation Application

JavaScript isn't enabled in your browser, so this file can't be opened. Enable and reload.

Before filling out this form, see the CFP (https://wimlworkshop.org/icml2021/cfp/) for instructions.

IMPORTANT NOTE: This form does not constitute registration for the WiML Un-Workshop. To attend the un-workshop, you need to register for ICML at https://icml.cc.

Data usage and sharing:

- You will be asked if you allow WiML to aggregate and anonymize your responses for use in WiML reports and publicity materials.
- You will be asked if you consent to specific information being shared with WiML sponsors.
Contact workshop@wimlworkshop.org if you have any questions.

First name *

Last name *

Email (same as your ICML website login: https://icml.cc/accounts/login) *

Position *

E.g. Statistics PhD student, Assistant Professor of Information Science

Affiliation (name of university, employer, etc.) *

If you have multiple affiliations, provide all of them.

Where is your home institution? *

North America

Central America, South America, the Caribbean

Western Europe

Eastern Europe

Africa

Middle East

Asia

Australia, Oceania

Pronouns:

The main format of the un-workshop is breakout sessions. Check all topics you are interested in participating in. We will use this information to schedule sessions to minimize conflict. *

Supervised Learning

Unsupervised Learning, Self-Supervised Learning

Deep Learning

Representation Learning

Reinforcement Learning and Planning

Optimization, Learning Theory

Probabilistic Methods, Generative Models, GANs

Causal Learning

Meta-Learning, Transfer Learning, Multi-Task Learning, Domain Adaptation

Few-shot Learning, Zero-shot Learning

Trustworthy ML: safety, robustness, transparency, fairness, privacy, interpretability

Computer Vision

Audio and Speech Processing

Natural Language Processing

Time Series Analysis

Robotics

Applications: Computational Biology or Neuroscience

Applications: Physical Sciences

Applications: Healthcare, Social good, Climate science

Deployment of AI/ML systems

Machine Learning for Embedded Systems

Information Theory and Machine Learning

Deep Learning for Perception

Federated Learning

Deep Learning for Compression

Required

Select 1 timezone that works best for you. *

If you would like to share your resume with WiML sponsors, submit it in the link below. Deadline: July 18.

Link: https://forms.gle/wkg9z9TpAyrTxfGfA. To submit your resume, you should identify primarily as a woman and/or nonbinary.

Would you like to share selected information with WiML sponsors listed here (https://wimlworkshop.org/partners/) and ICML organizers? *

Please do not share my information.

You may share my information (name, email, current position, institution, topics you are interested in attending, attendance at this WiML event) with WiML sponsors and ICML organizers.

I agree to abide by the WiML Code of Conduct (http://wimlworkshop.org/conduct/). *

Yes

Required

Clear form

Never submit passwords through Google Forms.

This form was created inside of Women in Machine Learning. Report Abuse

Forms