발행물

전체 논문

58

41

Data Cleaning for Accurate, Fair, and Robust Models: A Big Data - AI Integration Approach
K. Tae, Y. Roh, Y. Oh, H. Kim, S. E. Whang
3rd Int'l Workshop on Data Management for End-to-End Machine Learning, DEEM @ ACM SIGMOD, 2019

42

Data Validation for Machine Learning
E. Breck, N. Polyzotis, S. Roy, S. E. Whang, M. Zinkevich
MLSys Conference, 2019

43

Slice Finder: Automated Data Slicing for Model Validation
Y. Chung, T. Kraska, N. Polyzotis, K. Tae, S. E. Whang
IEEE Int'l Conf. on Data Engineering (ICDE), 2019

44

FR-Train: A Mutual Information-based Approach to Fair and Robust Training
Y. Roh, K. Lee, S. E. Whang, C. Suh
ICML, 2020

45

Open-world COVID-19 Data Visualization (Extended Abstract)
H. Hwang, S. E. Whang
DMAH @ VLDB Workshop, 2020

46

FairBatch: Batch Selection for Model Fairness [Talk][Slides][Code]
Y. Roh, K. Lee, S. E. Whang, C. Suh
9th Int'l Conference on Learning Representations (ICLR), 2021

47

Machine Learning Robustness, Fairness, and their Convergence (Tutorial) [Talk][Homepage][Slides]
J. Lee, Y. Roh, H. Song, S. E. Whang
27th ACM SIGKDD Int'l Conf. on Knowledge Discovery and Data Mining (KDD), 2021

48

Sample Selection for Fair and Robust Training [Talk][Slides][Code]
Y. Roh, K. Lee, S. E. Whang, C. Suh
35th Annual Conference on Neural Information Processing Systems (NeurIPS), 2021

49

Slice Tuner: A Selective Data Acquisition Framework for Accurate and Fair Machine Learning Models [Talk][Slides][Code]
K. Tae, S. E. Whang
2021 ACM SIGMOD Int'l Conf. on Management of Data (SIGMOD), 2021

50

lection for Model Fairness
Y. Roh, K. Lee, S. E. Whang, C. Suh
ICLR, 2021