Venkatanathan Varadarajan
Venkatanathan Varadarajan
Oracle Labs
Verified email at - Homepage
Cited by
Cited by
Aerie: Flexible file-system interfaces to storage-class memory
H Volos, S Nalli, S Panneerselvam, V Varadarajan, P Saxena, MM Swift
Proceedings of the Ninth European Conference on Computer Systems, 1-14, 2014
Resource-freeing attacks: improve your cloud performance (at your neighbor's expense)
V Varadarajan, T Kooburat, B Farley, T Ristenpart, MM Swift
Proceedings of the 2012 ACM conference on Computer and communications …, 2012
A Placement Vulnerability Study in Multi-tenant Public Clouds
V Varadarajan, Y Zhang, T Ristenpart, M Swift
24th USENIX Security Symposium, 913--928, 2015
More for your money: Exploiting performance heterogeneity in public clouds
B Farley, A Juels, V Varadarajan, T Ristenpart, KD Bowers, MM Swift
Proceedings of the Third ACM Symposium on Cloud Computing, 1-14, 2012
Scheduler-based Defenses against Cross-VM Side-channels
V Varadarajan, T Ristenpart, M Swift
23rd USENIX Security Symposium (USENIX Security 14), 2014
A many-core architecture for in-memory data processing
SR Agrawal, S Idicula, A Raghavan, E Vlachos, V Govindaraju, ...
Proceedings of the 50th Annual IEEE/ACM International Symposium on …, 2017
Oracle automl: a fast and predictive automl pipeline
A Yakovlev, HF Moghadam, A Moharrer, J Cai, N Chavoshi, ...
Proceedings of the VLDB Endowment 13 (12), 3166-3180, 2020
Algorithm-specific neural network architectures for automatic machine learning model selection
S Agrawal, S Idicula, V Varadarajan, N Agarwal
US Patent 11,544,494, 2023
Determining instances to maintain on at least one cloud responsive to an evaluation of performance characteristics
A Juels, KD Bowers, B Farley, V Varadarajan, T Ristenpart, MM Swift
US Patent 9,128,739, 2015
Gradient-based auto-tuning for machine learning and deep learning models
V Varadarajan, S Idicula, S Agrawal, N Agarwal
US Patent 11,176,487, 2021
Rapid: In-memory analytical query processing engine with extreme performance per watt
C Balkesen, N Kunal, G Giannikis, P Fender, S Sundara, F Schmidt, ...
Proceedings of the 2018 International Conference on Management of Data, 1407 …, 2018
Using meta-learning for automatic gradient-based hyperparameter optimization for machine learning and deep learning models
V Varadarajan, S Agrawal, S Idicula, N Agarwal
US Patent App. 15/914,883, 2019
Scalable and efficient distributed auto-tuning of machine learning and deep learning models
V Varadarajan, S Idicula, S Agrawal, N Agarwal
US Patent 11,120,368, 2021
Game theoretic resistance to denial of service attacks using hidden difficulty puzzles
H Narasimhan, V Varadarajan, CP Rangan
Information Security, Practice and Experience: 6th International Conference …, 2010
Using hyperparameter predictors to improve accuracy of automatic machine learning model selection
HF Moghadam, S Agrawal, V Varadarajan, A Yakovlev, S Idicula, ...
US Patent 11,620,568, 2023
Predicting machine learning or deep learning model training time
A Yakovlev, V Varadarajan, S Agrawal, HF Moghadam, S Idicula, ...
US Patent 11,429,895, 2022
Fast, predictive, and iteration-free automated machine learning pipeline
V Varadarajan, SR Agrawal, HF Moghadam, A Yakovlev, A Moharrer, ...
US Patent App. 17/086,204, 2021
Towards a Cooperative Defense Model Against Network Security Attacks.
H Narasimhan, V Varadarajan, CP Rangan
WEIS, 2010
Anomaly detection in SS7 control network using reconstructive neural networks
H Ahmadi, A Moharrer, V Varadarajan, V Akram, N Rai, R Hingorani, ...
US Patent 11,451,670, 2022
Efficient parallel algorithm for integral image computation for many-core CPUs
V Varadarajan, A Raghavan, S Idicula, N Agarwal
US Patent 10,529,049, 2020
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