Vijay Ekambaram

According to our database, Vijay Ekambaram authored at least 14 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation.

Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Kerstin Borras, Matthew R. Buckley, Erik Buhmann, Thorsten Buss, Renato Paulo Da Costa Cardoso, Anthony L. Caterini, Nadezda Chernyavskaya, Federico A. G. Corchia, Jesse C. Cresswell, Sascha Diefenbacher, Etienne Dreyer, Vijay Ekambaram, Engin Eren, Florian Ernst, Luigi Favaro, Matteo Franchini, Frank Gaede, Eilam Gross, Shih-Chieh Hsu, Kristina Jaruskova, Benno Käch, Jayant Kalagnanam, Raghav Kansal, Taewoo Kim, Dmitrii Kobylianskii, Anatolii Korol, William Korcari, Dirk Krücker, Katja Krüger, Marco Letizia, Shu Li, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Thandikire Madula, Peter McKeown, Isabell-A. Melzer-Pellmann, Vinicius Mikuni, Nam Nguyen, Ayodele Ore, Sofia Palacios Schweitzer, Ian Pang, Kevin Pedro, Tilman Plehn, Witold Pokorski, Huilin Qu, Piyush Raikwar, John A. Raine, Humberto Reyes-González, Lorenzo Rinaldi, Brendan Leigh Ross, Moritz A. W. Scham, Simon Schnake, Chase Shimmin, Eli Shlizerman, Nathalie Soybelman, Mudhakar Srivatsa, Kalliopi Tsolaki, Sofia Vallecorsa, Kyongmin Yeo, Rui Zhang

CoRR, 2024

Towards Unbiased Evaluation of Time-series Anomaly Detector.

Debarpan Bhattacharya, Sumanta Mukherjee, Chandramouli Kamanchi, Vijay Ekambaram, Arindam Jati, Pankaj Dayama

CoRR, 2024

Activations Through Extensions: A Framework To Boost Performance Of Neural Networks.

Chandramouli Kamanchi, Sumanta Mukherjee, Kameshwaran Sampath, Pankaj Dayama, Arindam Jati, Vijay Ekambaram, Dzung Phan

CoRR, 2024

Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series.

Vijay Ekambaram, Arindam Jati, Nam H. Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M. Gifford, Jayant Kalagnanam

CoRR, 2024

AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data.

Santosh Palaskar, Vijay Ekambaram, Arindam Jati, Neelamadhav Gantayat, Avirup Saha, Seema Nagar, Nam H. Nguyen, Pankaj Dayama, Renuka Sindhgatta, Prateeti Mohapatra, Harshit Kumar, Jayant Kalagnanam, Nandyala Hemachandra, Narayan Rangaraj

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

AutoMixer for Improved Multivariate Time-Series Forecasting on BizITOps Data.

Santosh Palaskar, Vijay Ekambaram, Arindam Jati, Neelamadhav Gantayat, Avirup Saha, Seema Nagar, Nam H. Nguyen, Pankaj Dayama, Renuka Sindhgatta, Prateeti Mohapatra, Harshit Kumar, Jayant Kalagnanam, Nandyala Hemachandra, Narayan Rangaraj

CoRR, 2023

Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting.

Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting.

Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Hierarchy-guided Model Selection for Time Series Forecasting.

Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami

CoRR, 2022

Distributed Incremental Machine Learning for Big Time Series Data.

Dhaval Salwala, Seshu Tirupathi, Brian Quanz, Wesley M. Gifford, Stuart Siegel, Vijay Ekambaram, Arindam Jati

Proceedings of the IEEE International Conference on Big Data, 2022

2020

Attention based Multi-Modal New Product Sales Time-series Forecasting.

Vijay Ekambaram, Kushagra Manglik, Sumanta Mukherjee, Surya Shravan Kumar Sajja, Satyam Dwivedi, Vikas Raykar

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2017

Tell Me More: Digital Eyes to the Physical World for Early Childhood Learning.

Vijay Ekambaram, Ruhi Sharma Mittal, Prasenjit Dey, Ravindranath Kokku, Aditya K. Sinha, Satya V. Nitta

Proceedings of the 10th International Conference on Educational Data Mining, 2017

2013

Appstrument - A Unified App Instrumentation and Automated Playback Framework for Testing Mobile Applications.

Vikrant Nandakumar, Vijay Ekambaram, Vivek Sharma

Proceedings of the Mobile and Ubiquitous Systems: Computing, Networking, and Services, 2013

Interest flooding reduction in Content Centric Networks.

Vijay Ekambaram, Krishna M. Sivalingam

Proceedings of the IEEE 14th International Conference on High Performance Switching and Routing, 2013