Program

PROGRAM

Monday, October 19th

Causal Reasoning Tutorial

09:00

Causal Reasoning Tutorial (abstract)

TBA

12:30

AutoML and interpretability: powering the machine learning revolution in healthcare (abstract)

Methodology

14:00	Yu Gui ADAGES: adaptive aggregation with stability for distributed feature selection (abstract)
14:20	Chenglin Fan and Ping Li Classification Acceleration via Merging Decision Trees (abstract)
14:40	Sarah Tan, Matvey Soloviev, Giles Hooker and Martin T. Wells Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable (abstract)
15:00	Miguel Carreira-Perpinan and Arman Zharmagambetov Ensembles of bagged TAO trees consistently improve over Random Forests, AdaBoost and Gradient Boosting (abstract)

Fairness, Privacy, Interpretability

15:45	Collin Burns, Jesse Thomason and Wesley Tansey Interpreting Black Box Models via Hypothesis Testing (abstract)
16:05	Ruobin Gong and Xiao-Li Meng Congenial Differential Privacy under Mandated Disclosure (abstract)
16:25	Roland Maio and Augustin Chaintreau Incentives Needed for Low-Cost Fair Data Reuse (abstract)
16:45	Isabella Grasso, David Russell, Jeanna Matthews, Abigail Matthews and Nick Record Applying Algorithmic Accountability Frameworks withDomain-specific Codes of Ethics: A Case Study in EcosystemForecasting for Shellfish Toxicity in the Gulf of Maine (abstract)

Tuesday, October 20th

Fairness, Privacy, and Ethics in Data Science Tutorial

09:00

Fairness, Privacy, and Ethics in Data Science Tutorial (abstract)

TBA

12:30

Semantic Scholar, NLP, and the Fight Against COVID-19 (abstract)

Data Science Theory

14:00	Alex Fout, Bailey Fosdick and Matthew Hitt Non-Uniform Sampling of Fixed Margin Binary Matrices (abstract)
14:20	Claire Mathieu and Michel De Rougemont Large very dense subgraphs in a stream of edges (abstract)
14:40	Xiangyi Chen, Xiaoyun Li and Ping Li Toward Communication Efficient Adaptive Gradient Method (abstract)
15:00	Tianyu Wang, Weicheng Ye, Dawei Geng and Cynthia Rudin Towards Practical Lipschitz Bandits (abstract)
15:20	Devavrat Shah, Varun Somani, Qiaomin Xie and Zhi Xu On Reinforcement Learning for Turn-based Zero-sum Markov Games (abstract)

Foundations in Practice

16:00	Ryan Bernstein, Matthijs Vákár and Jeannette Wing Transforming Probabilistic Programs for Model Checking (abstract)
16:20	Haitian Chen, Bai Jiang and Hao Chen StyleCAPTCHA: CAPTCHA based on style-transferred images to defend against Deep Convolutional Networks (abstract)
16:40	Lina Lin, Mathias Drton and Ali Shojaie Statistical significance in high-dimensional linear mixed models (abstract)
17:00	Thanh Le and Vasant Honavar Dynamical Gaussian Process Latent Variable Model for Representation Learning from Longitudinal Data (abstract)