Kraska, Tim

The Case for Learned Index Structures

Kraska, T., Beutel, A., Chi, E. H., Dean, J., & Polyzotis, N. (2018) · Proceedings of the 2018 International Conference on Management of Data

Advanced Database Systems and QueriesAlgorithms and Data Compression

Cited by 956

Superneurons: dynamic GPU memory management for training deep neural networks

Wang, L., Ye, J., Zhao, Y., Wu, W., Li, A., Song, S. L., Xu, Z., & Kraska, T. (2018) · Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 175

Slice Finder: Automated Data Slicing for Model Validation

Chung, Y., Kraska, T., Polyzotis, N., Tae, K. H., & Whang, S. E. (2019) · 2019 IEEE 35th International Conference on Data Engineering (ICDE)

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 83

Dark Data: Are we solving the right problems?

Cafarella, M., Ilyas, I. F., Kornacker, M., Kraska, T., & Re, C. (2016) · 2016 IEEE 32nd International Conference on Data Engineering (ICDE)

Big Data and Business IntelligenceData Quality and Management

Cited by 16

Recursive Language Models

Zhang, A. L., Kraska, T., & Khattab, O. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1