Publications
Papers and other publications on which I participated.
Papers
- Smith, Micah J., Carles Sala, James Max Kanter, and Kalyan Veeramachaneni. 2020. “The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development.” In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, 785–800. SIGMOD ’20. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3318464.3386146. Details
- Alnegheimish, Sarah, Dongyu Liu, Carles Sala, Laure Berti-Equille, and Kalyan Veeramachaneni. 2022. “Sintel: A Machine Learning Framework to Extract Insights from Signals.” In Proceedings of the 2022 International Conference on Management of Data, 1855–65. SIGMOD ’22. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3514221.3517910. Details
Collaborations
- Zhang, Kevin Alex, Alfredo Cuesta-Infante, Lei Xu, and Kalyan Veeramachaneni. 2019. “SteganoGAN: High Capacity Image Steganography with GANs.” CoRR abs/1901.03892. http://arxiv.org/abs/1901.03892. Details
- Xu, Lei, Maria Skoularidou, Alfredo Cuesta-Infante, and Kalyan Veeramachaneni. 2019. “Modeling Tabular Data Using Conditional GAN.” CoRR abs/1907.00503. http://arxiv.org/abs/1907.00503. Details
- Patki, N., R. Wedge, and K. Veeramachaneni. 2016. “The Synthetic Data Vault.” In 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 399–410. https://doi.org/10.1109/DSAA.2016.49. Details
Other
- Xue, William. 2018. “A Flexible Framework for Composing End to End Machine Learning Pipelines.” Master's thesis, Cambridge, Massachusetts: Massachusetts Institute of Technology. Details
- Gustafson, Laura. 2018. “Bayesian Tuning and Bandits: An Extensible, Open Source Library for AutoML.” Master's thesis, Cambridge, Massachusetts: Massachusetts Institute of Technology. Details
- Montanez, Andrew. 2018. “SDV: An Open Source Library for Synthetic Data Generation.” Master's thesis, Cambridge, Massachusetts: Massachusetts Institute of Technology. Details