The 13th WiML Workshop is co-located with NIPS in Montreal, Quebec on Monday, December 3rd, 2018.
The workshop is a one-day event with invited speakers, oral presentations, and posters. The event brings together faculty, graduate students, and research scientists for an opportunity to connect and exchange ideas. There will be a panel discussion and a mentoring session to discuss current research trends and career choices in machine learning. Underrepresented minorities and undergraduates interested in pursuing machine learning research are encouraged to participate. While all presenters will identify primarily as female, all genders are invited to attend.
- September 7th, 2018 11:59pm PST – Abstract submission deadline
- October 15th, 2018 – Notification of abstract acceptance
- TBA – Travel grant application deadline
- TBA – Registration Deadline
- December 3rd, 2018 – Workshop Day
We strongly encourage students, post-docs and researchers who primarily identify as women or nonbinary in all areas of machine learning to submit an abstract describing new, previously, or concurrently published research. We welcome abstract submissions, in theory, methodology, as well as applications. Abstracts may describe completed research or work-in-progress. While the presenting author need not be the first author of the work, we encourage authors to highlight the contribution of women — particularly the presenting author — in the abstract.
Authors of accepted abstracts will be asked to present their work in a poster session. A few authors will be selected to give 15 minute oral presentations. Submissions will be peer-reviewed in a double-blind setting. Authors will be automatically added to the reviewer pool and asked to review. Student and post-doc authors who review for WiML will be eligible for travel awards.
Submission page: WiML 2018 CMT
- Abstracts must not include identifying information
- Abstracts must be no more than 1 page (including any references, tables, and figures) submitted as a PDF in NIPS format.
- Upload the PDF, do not paste in the abstract box.
- Do not include any supplementary files with your submission.
- Your abstract should stand alone, without linking to a longer paper or supplement.
- You should convey motivation and give some technical details of the approach used.
- While we appreciate that space is limited, some experimental results are likely to improve reviewers’ opinions of your paper.
All accepted papers must be presented by the submitting author, or another author who identifies primarily as a woman or nonbinary. Abstracts will be reviewed by at least two reviewers plus an area chair, who will use the following criteria:
- Is this paper appropriate for WiML? I.e. Does it describe original research in Machine Learning or related fields?
- Does the abstract describe work that is novel and/or an interesting application?
- Does the abstract adequately convey the material that will be presented?
Examples of accepted abstracts from previous years. Due to the volume of submissions anticipated, we are unable to review any submitted materials besides the requested abstract.
Travel Awards are available for presenting authors only. To qualify, the author must be a student or postdoc, their abstract must be accepted, and they must volunteer to serve as a reviewer for WiML. The amount of the travel award varies by the author’s geographical location and the total amount of funding WiML receives from our sponsors. In the past awards ranging from $300-$900 have been granted. All travel grants are administered as refunds and no funding is allocated before the conference.
If you are interested in being an area chair, please email firstname.lastname@example.org with subject line “Area Chair for WiML 2018”. The role of area chairs is to evaluate the reviews, write a final meta-review and suggest acceptance/reject decisions for each abstract. We expect each area chair to be responsible for 10 short abstracts with each abstract having a maximum word limit of 500 words.
- Audrey Durand (McGill University)
- Aude Hofleitner (Facebook)
- Nyalleng Moorosi (CSIR)
- Sarah Poole (Stanford University)
- Amy Zhang (McGill University / Facebook AI Research)