Vijay Ekambaram

19 papers A* 5B 2C 2Misc 1Journal 9
YearRankTypeTitle / Venue / Authors
2025 J jnl
Memory-Efficient Batching for Time Series Transformer Training: A Systematic Evaluation.
Algorithms
Phanwadee Sinthong, Nam Nguyen, Vijay Ekambaram, Arindam Jati, Jayant Kalagnanam, Peeravit Koad
2025 J jnl
TSPulse: Dual Space Tiny Pre-Trained Models for Rapid Time-Series Analysis.
CoRR
Vijay Ekambaram, Subodh Kumar, Arindam Jati, Sumanta Mukherjee, Tomoya Sakai, Pankaj Dayama, Wesley M. Gifford, Jayant Kalagnanam
2025 Misc conf
Towards Unbiased Evaluation of Time-series Anomaly Detector.
ICASSP
Debarpan Bhattacharya, Sumanta Mukherjee, Chandramouli Kamanchi, Vijay Ekambaram, Arindam Jati, Pankaj Dayama
2024 J jnl
Activations Through Extensions: A Framework To Boost Performance Of Neural Networks.
CoRR
Chandramouli Kamanchi, Sumanta Mukherjee, Kameshwaran Sampath, Pankaj Dayama, Arindam Jati, Vijay Ekambaram, Dzung Phan
2024 A* conf
AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data.
AAAI
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
2024 J jnl
CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation.
CoRR
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
2024 A* conf
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series.
NeurIPS
Vijay Ekambaram, Arindam Jati, Pankaj Dayama, Sumanta Mukherjee, Nam Nguyen, Wesley M. Gifford, Chandra Reddy, Jayant Kalagnanam
2024 J jnl
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series.
CoRR
Vijay Ekambaram, Arindam Jati, Nam H. Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M. Gifford, Jayant Kalagnanam
2024 J jnl
Towards Unbiased Evaluation of Time-series Anomaly Detector.
CoRR
Debarpan Bhattacharya, Sumanta Mukherjee, Chandramouli Kamanchi, Vijay Ekambaram, Arindam Jati, Pankaj Dayama
2023 J jnl
AutoMixer for Improved Multivariate Time-Series Forecasting on BizITOps Data.
CoRR
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
2023 A* conf
Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting.
KDD
Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami
2023 A* conf
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting.
KDD
Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
2023 J jnl
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting.
CoRR
Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
2022 B conf
Distributed Incremental Machine Learning for Big Time Series Data.
IEEE Big Data
Dhaval Salwala, Seshu Tirupathi, Brian Quanz, Wesley M. Gifford, Stuart Siegel, Vijay Ekambaram, Arindam Jati
2022 J jnl
Hierarchy-guided Model Selection for Time Series Forecasting.
CoRR
Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami
2020 A* conf
Attention based Multi-Modal New Product Sales Time-series Forecasting.
KDD
Vijay Ekambaram, Kushagra Manglik, Sumanta Mukherjee, Surya Shravan Kumar Sajja, Satyam Dwivedi, Vikas Raykar
2017 B conf
Tell Me More: Digital Eyes to the Physical World for Early Childhood Learning.
EDM
Vijay Ekambaram, Ruhi Sharma Mittal, Prasenjit Dey, Ravindranath Kokku, Aditya K. Sinha, Satya V. Nitta
2013 C conf
Appstrument - A Unified App Instrumentation and Automated Playback Framework for Testing Mobile Applications.
MobiQuitous
Vikrant Nandakumar, Vijay Ekambaram, Vivek Sharma
2013 C conf
Interest flooding reduction in Content Centric Networks.
HPSR
Vijay Ekambaram, Krishna M. Sivalingam