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Kalyan Veeramachaneni
Kalyan Veeramachaneni
Principal Research Scientist, Massachusetts Institute of Technology
Verified email at csail.mit.edu
Title
Cited by
Cited by
Year
Modeling tabular data using conditional gan
L Xu, M Skoularidou, A Cuesta-Infante, K Veeramachaneni
Advances in neural information processing systems 32, 2019
10192019
Opentuner: An extensible framework for program autotuning
J Ansel, S Kamil, K Veeramachaneni, J Ragan-Kelley, J Bosboom, ...
Proceedings of the 23rd international conference on Parallel architectures …, 2014
6822014
Fitness-distance-ratio based particle swarm optimization
T Peram, K Veeramachaneni, CK Mohan
Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No …, 2003
6782003
The synthetic data vault
N Patki, R Wedge, K Veeramachaneni
2016 IEEE international conference on data science and advanced analytics …, 2016
5192016
Deep feature synthesis: Towards automating data science endeavors
JM Kanter, K Veeramachaneni
2015 IEEE international conference on data science and advanced analytics …, 2015
4832015
AI^ 2: training a big data machine to defend
K Veeramachaneni, I Arnaldo, V Korrapati, C Bassias, K Li
2016 IEEE 2nd international conference on big data security on cloud …, 2016
3492016
Synthesizing tabular data using generative adversarial networks
L Xu, K Veeramachaneni
arXiv preprint arXiv:1811.11264, 2018
2822018
Tadgan: Time series anomaly detection using generative adversarial networks
A Geiger, D Liu, S Alnegheimish, A Cuesta-Infante, K Veeramachaneni
2020 ieee international conference on big data (big data), 33-43, 2020
2592020
Optimization using particle swarms with near neighbor interactions
K Veeramachaneni, T Peram, C Mohan, L Osadciw
Genetic and Evolutionary Computation—GECCO 2003, 200-200, 2003
2322003
SteganoGAN: High capacity image steganography with GANs
KA Zhang, A Cuesta-Infante, L Xu, K Veeramachaneni
arXiv preprint arXiv:1901.03892, 2019
2242019
Likely to stop? predicting stopout in massive open online courses
C Taylor, K Veeramachaneni, UM O'Reilly
arXiv preprint arXiv:1408.3382, 2014
1932014
Distributed, multi-model, self-learning platform for machine learning
WD Drevo, KK Veeramachaneni, U O'reilly
US Patent App. 14/598,628, 2016
1882016
An adaptive multimodal biometric management algorithm
K Veeramachaneni, LA Osadciw, PK Varshney
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2005
1852005
Automl to date and beyond: Challenges and opportunities
SK Karmaker, MM Hassan, MJ Smith, L Xu, C Zhai, K Veeramachaneni
ACM Computing Surveys (CSUR) 54 (8), 1-36, 2021
1632021
ATM: A distributed, collaborative, scalable system for automated machine learning
T Swearingen, W Drevo, B Cyphers, A Cuesta-Infante, A Ross, ...
2017 IEEE international conference on big data (big data), 151-162, 2017
1422017
Autotuning algorithmic choice for input sensitivity
Y Ding, J Ansel, K Veeramachaneni, X Shen, UM O’Reilly, ...
ACM SIGPLAN Notices 50 (6), 379-390, 2015
1382015
Transfer learning for predictive models in massive open online courses
S Boyer, K Veeramachaneni
Artificial Intelligence in Education: 17th International Conference, AIED …, 2015
1192015
Atmseer: Increasing transparency and controllability in automated machine learning
Q Wang, Y Ming, Z Jin, Q Shen, D Liu, MJ Smith, K Veeramachaneni, ...
Proceedings of the 2019 CHI conference on human factors in computing systems …, 2019
1082019
Building predictive models via feature synthesis
I Arnaldo, UM O'Reilly, K Veeramachaneni
Proceedings of the 2015 annual conference on genetic and evolutionary …, 2015
992015
DropoutSeer: Visualizing learning patterns in Massive Open Online Courses for dropout reasoning and prediction
Y Chen, Q Chen, M Zhao, S Boyer, K Veeramachaneni, H Qu
2016 IEEE Conference on Visual Analytics Science and Technology (VAST), 111-120, 2016
922016
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