Intelligent Scaling in Amazon Redshift
SIGMOD 2024, 2024
Vikram Nathan, Vikramank Singh, Zhengchun Liu, Mohammad Rahman, Andreas Kipf, Dominik Horn, Davide Pagano, Gaurav Saxena, Balakrishnan (Murali) Narayanaswamy, Tim Kraska
Publications
Panda: Performance debugging for databases using LLM agents
CIDR 2024, 2024
Vikramank Singh, Kapil Eknath Vaidya, Vinayshekhar Bannihatti Kumar, Sopan Khosla, Murali Narayanaswamy, Rashmi Gangadharaiah, Tim Kraska
Predict-and-Critic: Accelerated End-to-End Predictive Control for Cloud Computing through Reinforcement Learning
ArXiv Preprint, 2023
Kaustubh Sridhar, Vikramank Singh, Balakrishnan Narayanaswamy, Abishek Sankararaman
FITNESS:(Fine Tune on New and Similar Samples) to detect anomalies in streams with drift and outliers
International Conference on Machine Learning (ICML), 2022
Abishek Sankararaman, Balakrishnan Narayanaswamy, Vikramank Y Singh, Zhao Song
C-GATS: Conditional generation of anomalous time series
Neural Information Processing Systems (NeurIPS), SyntheticData4ML Workshop, 2022
Vikramank Singh, Abishek Sankararaman, Balakrishnan Murali Narayanaswamy, Zhao Song
PDQN - A Deep Reinforcement Learning Method for Planning with Long Delays: Optimization of Manufacturing Dispatching
OpenReview, 2021
David C Jenkins, René Arendt Sørensen, Vikramank Singh, Philip Kaminsky, Anil Aswani, Ramakrishna Akella