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  • wiml
  • October 28, 2016

The 2020 WiML Un-Workshop at ICML will be held on Monday, July 13th, 2020 virtually.

All participants are required to abide by the WiML code of conduct.


Schedule


The program will include the following line-up of invited speakers:


2020 Invited Speakers
Monday, July 13th, 2020
Time (GMT/UTC) Event
06:45 – 07:00 Introduction and opening remarks
07:00 – 07:35 Invited talk – Sara van de Geer
07:35 – 08:35 Breakout sessions #1
08:35 – 08:50 Virtual coffee break #1
08:50 – 09:25 Invited talk – Naila Murray
09:25 – 10:25 Breakout sessions #2
10:25 – 11:10 Sponsor Expo: Presentations by QuantumBlack, Netflix and IBM
11:10 – 15:10 Break
15:10 – 16:10 Sponsor Expo: Presentations by Google, Apple, DeepMind and Facebook
16:10 – 16:45 Invited talk – Nancy Reid
16:45 – 17:45 Breakout sessions #3
17:45 – 18:00 Virtual coffee break #2
18:00 – 18:35 Invited talk – Doina Precup
18:35 – 19:35 Breakout sessions #4
19:35 – 20:35 Panel discussion
20:35 – 20:50 Closing remarks
21:00 – 23:00 Joint affinity groups poster session
For more detailed version of the breakout sessions (for example, seeing affiliations) please use this link.

Breakout session #1, 7:35 AM – 8:35 AM GMT

ID Session title Leaders Facilitators
1.1 Inference of Cross-lingual Language Models Gagana Coolga, Stuti Gupta Akash Smaran
1.2 Predicting Health with Limited Resources: Issues and Opportunities Mary-Anne Hartley, Danielle Belgrave Berthine Nyunga
1.3 Deep Learning for Natural Language Processing in Low Resource settings Surangika Ranathunga, Rishemjit Kaur, Annie En-Shiun Lee Marjana Skenduli, Mehreen Alam
1.4 AI and Creativity: Generative Art Aneta Neumann, Frehiwot Girmay Aparna Akula, Tina Raissi

Breakout session #2, 9:25AM – 10:25AM GMT

ID Session title Leaders Facilitators
2.1 Well-specified Scalable Models with Variational Inference Ines Krissaane, Samrudhdhi Rangrej Laya Rafiee
2.2 Bayesian Optimization Alessandra Tosi, Maren Mahsereci, Beyza Ermiş Salomey Osei
2.3 AI and Morality: Teaching Human Morality to Machines Frehiwot Girmay, Aneta Neumann Georgie Kennedy, Paula Hall
2.4 Future of data: How will data diversity become a
requirement for training AI models
Adepeju Oshisanya, Allison Gardner, Aylin Cakiroglu, Simone Larsson Celine Lature

Breakout session #3, 4:45PM – 5:45PM GMT

ID Session title Leaders Facilitators
3.1 Healthcare and Machine Learning: real world applications and challenges Olga Liakhovich, Tempest van Schaik, Summer Elasady, Bianca Furtuna Katie Claveau
3.2 Recommender System Research in Industry Ghazal Fazelnia, Zahra Nazari, Mozhgan Saeidi Krystal Maughan, Sneha Srinivasan
3.3 Applied Category Theory Tai-Danae Bradley Melanie Weber
3.4 Mining biological and biomedical data with graph-based
algorithms
Natalie Stanley, Huda Nassar, Ina Stelzer Jolene Ranek
3.5 Feminist Perspectives for Machine Learning & Computer Vision Fatemehsadat Mireshghallah, Srishti Yadav, Mary Anne Smart Jin (Alice) Qixuan
3.6 Tackling Climate Change with Machine Learning Priya Donti, Sasha Luccioni David Rolnick
3.7 Not Just Another Application: Applications for Social Good Jennifer Hobbs, Saba Dadsetan, Naira Hovakimyan Tania Lorido Botran, Lori Liu
3.8 Optimization Challenges of Generative Adversarial Networks Reyhane Askari Hemmat, Alexia Jolicoeur-Martineau, Laya Rafiee Xing Han
3.9 Challenges and practices in deploying AI in Medical Imaging Weiwei Zong, Manju Liu Zhen Sun
3.10 Entangled Conversations on Disentangled Representations (EnCoDR) Chhavi Yadav, Irina Higgins, Jovana Mitrović Laure Delisle, Niveditha Kalavakonda

Breakout session #4, 6:35PM – 7:35PM GMT

ID Session title Leaders Facilitators
4.1 Un-Bookclub: Race After Technology Anoush Najarian, Ishaani, Aleshia Hayes Sindhuja Parimalarangan, Louvere Walker-Hannon
4.2 Fairness and bias in ML and NLP Swetasudha Panda, Emily Black, Xueru Zhang Shikha Bordia
4.3 Coping with sample inefficiency of deep-reinforcement learning (DRL) for embodied AI Vidhi Jain, Simin Liu Ganesh Iyer
4.4 Performative Prediction: When Predictions Impact the Predicted Celestine Mendler-Dünner, Tijana Zrnic Juan Carlos Perdomo
4.5 Robust Machine Learning with Bad Training Data Sergul Aydore, Haleh Akrami Berna Kabadayi
4.6 Machine Learning for Neuroimaging Elvisha Dhamala, Meenakshi Khosla Carmen Khoo
4.7 A Review of Early Exit Training and Inference techniques Vaidheeswaran Archana, Sherin Mathews, Yashika Sharma Zahra Vaseqi
4.8 Continual Reinforcement Learning Khimya Khetarpal, Rose E. Wang, Feryal Behbahani Arundhati Banerjee
4.9 Uncertainty Estimation in Bayesian Deep Learning Polina Kirichenko, Melanie F. Pradier, Weiwei Pan Ana-Denisa Secuiu
4.10 Towards children-aware machine learning with a focus on NLP challenges and applications Belen Saldias, Safinah Ali Tamara Covacevich, Clare Liu

Sponsor Expo Presentations

ID Sponsor Speaker Title
1 QuantumBlack Maren Eckhoff AI for Good
2 Netflix Maria Dimakopoulou Slate Bandit Learning & Evaluation
3 IBM Lisa Amini Research AI
4 Apple Lizi Ottens Machine Learning at Apple
5 DeepMind Meire Fortunato DeepMind at WiML Un-workshop
6 Facebook Kalesha Bullard Learning to Communicate Nonverbally for Embodied Agent Populations
7 Google Jennifer Wei Machine Learning for Smell: Learning Generalizable Perceptual Representations of Small Molecules

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