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Vijay Ekambaram
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2020 – today
- 2024
- [c8]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:
AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data. AAAI 2024: 22962-22968 - [i7]Vijay Ekambaram, Arindam Jati, Nam H. Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M. Gifford, Jayant Kalagnanam:
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series. CoRR abs/2401.03955 (2024) - [i6]Chandramouli Kamanchi, Sumanta Mukherjee, Kameshwaran Sampath, Pankaj Dayama, Arindam Jati, Vijay Ekambaram, Dzung Phan:
Activations Through Extensions: A Framework To Boost Performance Of Neural Networks. CoRR abs/2408.03599 (2024) - [i5]Debarpan Bhattacharya, Sumanta Mukherjee, Chandramouli Kamanchi, Vijay Ekambaram, Arindam Jati, Pankaj Dayama:
Towards Unbiased Evaluation of Time-series Anomaly Detector. CoRR abs/2409.13053 (2024) - [i4]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:
CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. CoRR abs/2410.21611 (2024) - 2023
- [c7]Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam:
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting. KDD 2023: 459-469 - [c6]Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami:
Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting. KDD 2023: 891-900 - [i3]Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam:
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting. CoRR abs/2306.09364 (2023) - [i2]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:
AutoMixer for Improved Multivariate Time-Series Forecasting on BizITOps Data. CoRR abs/2310.20280 (2023) - 2022
- [c5]Dhaval Salwala, Seshu Tirupathi, Brian Quanz, Wesley M. Gifford, Stuart Siegel, Vijay Ekambaram, Arindam Jati:
Distributed Incremental Machine Learning for Big Time Series Data. IEEE Big Data 2022: 2356-2363 - [i1]Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami:
Hierarchy-guided Model Selection for Time Series Forecasting. CoRR abs/2211.15092 (2022) - 2020
- [c4]Vijay Ekambaram, Kushagra Manglik, Sumanta Mukherjee, Surya Shravan Kumar Sajja, Satyam Dwivedi, Vikas Raykar:
Attention based Multi-Modal New Product Sales Time-series Forecasting. KDD 2020: 3110-3118
2010 – 2019
- 2017
- [c3]Vijay Ekambaram, Ruhi Sharma Mittal, Prasenjit Dey, Ravindranath Kokku, Aditya K. Sinha, Satya V. Nitta:
Tell Me More: Digital Eyes to the Physical World for Early Childhood Learning. EDM 2017 - 2013
- [c2]Vijay Ekambaram, Krishna M. Sivalingam:
Interest flooding reduction in Content Centric Networks. HPSR 2013: 205-210 - [c1]Vikrant Nandakumar, Vijay Ekambaram, Vivek Sharma:
Appstrument - A Unified App Instrumentation and Automated Playback Framework for Testing Mobile Applications. MobiQuitous 2013: 474-486
Coauthor Index
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