Behind the Curation of the NeurIPS 2019 Tutorials
An important part of the Neural Information Processing Systems (NeurIPS) conference is the excellent tutorial program. We are excited to announce this year’s line-up of outstanding tutorials. This guest blog post is written by the Tutorial Chairs for NeurIPS 2019, Danielle Belgrave and Alice Oh, to explain the behind-the-scenes process of inviting and selecting the tutorial speakers and topics.
Goals for this year’s tutorial program
The central goal of the tutorial program is to feature topics that are of interest to a sizable portion of the NeurIPS community. At the same time, we would like to have minimal topic overlap with the recent NeurIPS conferences as well as the International Conference on Machine Learning (ICML), the International Conference on Learning Representations (ICLR), and other conferences that are often attended by members of the NeurIPS community. Last but not least, we aim to have a program that includes fresh perspectives from speakers outside of our community. This is important because the NeurIPS community is expanding, and we are seeing cross-disciplinary research where machine learning (ML) methods are being used in other fields, as well as methods and ideas from other fields being applied to ML.
Equally important as the topics, the tutorial speakers should be leaders in their research areas. They should be experts who know the topic inside and out, and have demonstrated an ability to deliver that knowledge in understandable language and clear presentation. They should present information deep enough that those in the audience who are active researchers in related areas would still learn a lot. In addition, the tutorial speakers should cover beyond their own research to touch on other parts of the topic addressed because these tutorials are not focused research talks, but rather comprehensive talks that encompass multiple perspectives. That’s a lot to ask!
Prioritizing diversity and inclusion in ML is an important effort. Diversity goes beyond familiar dimensions such as age, seniority, gender, race, nationality, and current geographical location. Diversity is also about enriching the ML community by offering a broad range of perspectives on tackling challenges within ML and thinking about the implications for society. This might include prioritizing speakers and topics that have not received as much attention in recent years, but also including perspectives from outside the “mainstream” ML community who bring viewpoints that are of interest and benefit to the ML community. Diversity was therefore a key factor when selecting tutorial speakers and topics.
Process for selecting invited and proposed tutorials
Both tutorial chairs independently drew up a list of potential speakers and shared the list with each other. In coming up with our lists, we looked at the last few years’ publications, workshops, and tutorials presented at NeurIPS and at related venues. We also asked our colleagues for recommendations as well as conducting our own research. We then discussed each candidate from both lists. In reviewing the potential speakers, we read their papers to understand their expertise and watched their videos to appreciate their style of delivery. The well-known candidates were easier to review, as they had visibility within the ML community, either through presence in video lectures or long lists of publications. But we also took time to get to know (relatively) newer candidates. In making our shortlist, we also made sure that the candidates spanned a wide range of topics and did not retread recently covered ground.
We emailed the General Chair, Diversity & Inclusion Chairs, and the rest of the Organizing Committee for their comments on this shortlist. Following a few adjustments based on their input, we then emailed the potential speakers and asked whether they would be willing to give a NeurIPS tutorial.
2. Proposed Tutorials
On the 14th May 2019 we published an open call for tutorials on the NeurIPS website. Applications were open until June 11th. We received 46 proposals, and we selected a maximum of nine to be presented. Many of the proposals were excellent. We especially appreciated those that contained detailed plans and how the speakers would cover the proposed topics with sufficient depth and breadth. Many of the proposals contained links to speakers’ previous talks and lectures which were helpful, as were explanations of the experiences and roles of each speaker.
We also appreciated descriptions of the main papers and supplementary papers that would be covered, especially if that set of papers included more than one perspective on the topic. Again, each of the chairs independently selected a handful of proposals. We discussed these in depth, taking into account how they would work with the list of invited tutorials we had already chosen. Once we reached agreement, we spoke with the General Chair and the Diversity and Inclusion Chairs about the entire tutorial program.
NeurIPS 2019 Tutorials List
After all that hard work, we are proud and excited to announce the finalized list of tutorial speakers and topics for this year’s conference. This list is in alphabetical order of the title and does not reflect the order in which the tutorials will take place at the conference.
- Deep Learning with Bayesian Principles
- Efficient Processing of Deep Neural Network: from Algorithms to Hardware Architectures
- Human Behavior Modeling with Machine Learning: Opportunities and Challenges
Nuria Oliver, Albert Ali Salah
- Interpretable Comparison of Distributions and Models
Wittawat Jitkrittum, Dougal Sutherland, Arthur Gretton
- Language Generation: Neural Modeling and Imitation Learning Kyunghyun Cho, Hal Daume III
- Machine Learning for Computational Biology and Health
Anna Goldenberg, Barbara Engelhardt
- Reinforcement Learning: Past, Present, and Future Perspectives
- Representation Learning and Fairness
Moustapha Cisse, Sanmi Koyejo
- Synthetic Control
Alberto Abadie, Vishal Misra, Devavrat Shah
The tutorials are an integral part NeurIPS and play a unique role in the ML community. We are very grateful to everyone who helped us shape this year’s tutorials, especially those who submitted excellent proposals. We are extremely honored to serve in this important role, and we hope that you are as excited as we are about this year’s tutorial program. We are looking forward to seeing all of you, especially the tutorial speakers, in December!
Alice Oh, KAIST and Danielle Belgrave, Microsoft Research
NeurIPS 2019 Tutorial Chairs