FODS

Publications

2020

FODS '20: ACM-IMS Foundations of Data Science Conference, Virtual Event, USA, October 19-20, 2020 FODS (2020)
Chenglin Fan, Ping Li
Classification Acceleration via Merging Decision Trees. FODS (2020)
Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov
Ensembles of Bagged TAO Trees Consistently Improve over Random Forests, AdaBoost and Gradient Boosting. FODS (2020)
Lina Lin, Mathias Drton, Ali Shojaie
Statistical Significance in High-dimensional Linear Mixed Models. FODS (2020)
Tianyu Wang, Weicheng Ye, Dawei Geng, Cynthia Rudin
Towards Practical Lipschitz Bandits. FODS (2020)
Yu Gui
ADAGES: Adaptive Aggregation with Stability for Distributed Feature Selection. FODS (2020)
Mihaela van der Schaar
AutoML and Interpretability: Powering the Machine Learning Revolution in Healthcare. FODS (2020)
Claire Mathieu, Michel de Rougemont
Large Very Dense Subgraphs in a Stream of Edges. FODS (2020)
Roland Maio, Augustin Chaintreau
Incentives Needed for Low-Cost Fair Lateral Data Reuse. FODS (2020)
Alex Fout, Bailey K. Fosdick, Matthew P. Hitt
Non-Uniform Sampling of Fixed Margin Binary Matrices. FODS (2020)
Sarah Tan, Matvey Soloviev, Giles Hooker, Martin T. Wells
Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable. FODS (2020)
Ryan Bernstein, Matthijs Vákár, Jeannette Wing
Transforming Probabilistic Programs for Model Checking. FODS (2020)
Haitian Chen, Bai Jiang, Hao Chen
StyleCAPTCHA: CAPTCHA Based on Stylized Images to Defend against Deep Networks. FODS (2020)
Xiangyi Chen, Xiaoyun Li, Ping Li
Toward Communication Efficient Adaptive Gradient Method. FODS (2020)
Thanh Le, Vasant G. Honavar
Dynamical Gaussian Process Latent Variable Model for Representation Learning from Longitudinal Data. FODS (2020)
Collin Burns, Jesse Thomason, Wesley Tansey
Interpreting Black Box Models via Hypothesis Testing. FODS (2020)
Isabella Grasso, David Russell, Abigail Matthews, Jeanna N. Matthews, Nicholas R. Record
Applying Algorithmic Accountability Frameworks with Domain-specific Codes of Ethics: A Case Study in Ecosystem Forecasting for Shellfish Toxicity in the Gulf of Maine. FODS (2020)
Devavrat Shah, Varun Somani, Qiaomin Xie, Zhi Xu
On Reinforcement Learning for Turn-based Zero-sum Markov Games. FODS (2020)
Ruobin Gong, Xiao-Li Meng
Congenial Differential Privacy under Mandated Disclosure. FODS (2020)
Oren Etzioni
Semantic Scholar, NLP, and the Fight against COVID-19. FODS (2020)