New In ML workshop at NeurIPS 2021
Is this your first time to a top conference? Have you ever wanted your own work recognized by this huge and active community? Do you encounter difficulties in polishing your ideas, experiments, paper writing, etc? Then, this session is exactly for you!
This year, we are organizing the New in ML workshop, co-locating with NeurIPS 2021. We are targeting anyone who has not published a paper at the NeurIPS main conference yet. We invited top researchers to review your work and share with you their experience. The best papers will get oral presentations!
Our biggest goal is to help you publish papers at next year’s NeurIPS conference, and generally provide you with the guidance you need to contribute to ML research fully and effectively!
Within quota limits, the authors of the best accepted papers may be receiving the tickets to NeurIPS 2021, to be attributed according to merit and need.
It is a requirement to register for the NeurIPS 2021 conference in order to attend the workshops, socials and anything connected to the NeurIPS Conference platform, including this workshop.
Once your NeurIPS 2021 registration is active, it is not required to additionally register for this workshop in order to attend. However we would like to have an estimate of the number of attendees and their background. If you are interested in attending the New In ML workshop at NeurIPS 2021, please register with this link.
If you want to join the NewInML community, please leave your email address here: link.
Call For Papers
Since this is an exercise in writing good NeurIPS papers, the authors are requested to submit papers respecting the NeurIPS format and instructions: https://nips.cc/Conferences/2021/CallForPapers. All submissions must be in PDF format. Submissions are limited to nine content pages, including all figures and tables; additional pages containing the NeurIPS paper checklist and references are allowed. Shorter papers with enough good contents are also welcome. Submitted papers must respect the NeurIPS format, they must be anonymous and follow the NeurIPS template. Submissions that do not follow the format will be rejected. Appendix can be inserted at the end of the paper. We restrict submissions to first authors with no prior accepted publication at NeurIPS (main conference) and which are not under review or accepted elsewhere. Papers having been rejected before should be revised before submission to New In ML. We recommend sharing previous reviews with your new reviewers. Submitted papers will be reviewed by expert reviewers in a double-blind manner. Accepted papers could expect further coaching and mentorship if both reviewers and authors agree to communicate.
Generally speaking, the submitted papers do not need to be as good as a top conference publication. However we highly value works that are promising and novelties.
This will NOT count as an official NeurIPS publication, the NewInML 2021 workshop does not have a publication proceedings. Papers submitted can then be revised and submitted to NeurIPS 2022, but you should check the policy of other conferences if you want to re-submit elsewhere. We allow the submission of papers that have been submitted to another workshop in condition that the other workshop does not have a publication proceedings and this does not violate the policy of the other workshop. You are responsible to check the dual-submission policy of the other workshop and decide whether you can re-submit your paper to the NewInML 2021 workshop. Accepted papers will be listed on the workshop homepage if the authors do not issue an objection. If an accepted paper is also accepted by another workshop, the authors can decide which workshop they want to keep. If you need to withdraw your paper from the NewInML 2021 workshop, please contact us at contactnewinml (at) gmail.com.
Paper submission is through CMT platform: https://cmt3.research.microsoft.com/NewInML2021/Submission/Index
Contact us at contactnewinml (at) gmail.com if you encounter technical issues.
All topics related to machine learning are welcome. They include but not limited to:
- Computer Vision
- Natural Language Processing
- Graph Neural Networks
- Meta Learning
- Transfer Learning
- Reinforcement Learning
- Deep Learning Theory
- Deep Learning Interpretability
- Fairness and Privacy
- Automated Machine Learning
- Bayesian Machine Learning
- Causal Inference
- Adversarial Machine Learning
- Data, Competitions, Implementations, and Software
- Neuroscience and Cognitive Science
Paper submission deadline has been extended to October 1, 2021 AoE.
September 26, 2021 (Anywhere on Earth): Paper submission deadline
- October 1, 2021 (Anywhere on Earth): Paper submission deadline
- October 22, 2021 (Anywhere on Earth): Author notification of acceptance
- November 1, 2021 (Anywhere on Earth): SlidesLive upload deadline for speaker videos
- December 7, 2021: Session day
This will be a one-day online event.
Program ( time zone in New York, Eastern Standard Time, EST, UTC−5 ):
Tuesday December 7, 2021
|09:02 - 09:05||Opening address|
|09:05 - 09:50||Invited Talk Hung-Yi Lee (National Taiwan University)|
|09:50 - 14:00||Break|
|14:00 - 15:15||Invited Talk Oriol Vinyals (DeepMind)|
|15:15 - 16:15||Contributed Talks (10 min + 5 min questions for each paper)|
|16:15 - 17:30||Invited Talk Yale Song (Microsoft Research)|
Please register for the NeurIPS 2021 conference.
- Part 1 (09:02 - 09:50)
- Part 2 (14:00 - 17:30)
- Joint Affinity Poster Session (affinity-poster-room-1, 0:00 a.m. - 2:00 a.m., Tuesday December 7, 2021, UTC−5)
- MAML is a Noisy Contrastive Learner (Oral) Chia-Hsiang Kao, Wei-Chen Chiu, Pin-Yu Chen
- MAPLE: Microprocessor A Priori for Latency Estimation (Oral) Saad Abbasi, Alexander Wong, Mohammad Javad Shafiee
- XCI-Sketch: Extraction of Color Information from Images for Generation of Colored Outlines and Sketches (Oral) V Manushree, Sameer Saxena, Parna Chowdhury, MANISIMHA VARMA MANTHENA, Harsh Rathod, Ankita Ghosh, Sahil Khose
- Guided Evolution for Neural Architecture Search (Oral) Vasco Lopes, Miguel Santos, Bruno Degardin, Luís A. Alexandre
- Semantic Code Classification for Automated Machine Learning (Poster) Polina Guseva, Anastasia Drozdova
- Multiple Instance Learning for Brain Tumor Detection with Magnetic Resonance Spectroscopy Data (Poster) Diyuan Lu, Gerhard Kurz, Nenad Polomac, Iskra Gacheva, Elke Hattingen, Jochen Triesch
- A Data-driven Markov Chain Model for COVID-19 Transmission in South Korea (Poster) Sujin Ahn, Minhae Kwon
- Haozhe Sun ( LISN/CNRS/INRIA Université Paris-Saclay )
- Wenzhuo Liu ( IRT SystemX )
- Joseph Pedersen ( Rensselaer Polytechnic Institute )
- Zhen Xu ( 4Paradigm )
- Isabelle Guyon ( LISN/CNRS/INRIA Université Paris-Saclay, ChaLearn )
- Wei-Wei Tu ( 4Paradigm, ChaLearn )
Write us at: contactnewinml (at) gmail.com
Follow us on Twitter: @NewInML