Kalagnanam, Jayant

19 publications

ICLR 2026 TSPulse: Tiny Pre-Trained Models with Disentangled Representations for Rapid Time-Series Analysis Vijay Ekambaram, Subodh Kumar, Arindam Jati, Sumanta Mukherjee, Tomoya Sakai, Pankaj Dayama, Wesley M. Gifford, Jayant Kalagnanam

NeurIPS 2025 FailureSensorIQ: A Multi-Choice QA Dataset for Understanding Sensor Relationships and Failure Modes Christodoulos Constantinides, Dhaval C Patel, Shuxin Lin, Claudio Guerrero, Sunil Dagajirao Patil, Jayant Kalagnanam

AAAI 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

UAI 2024 Identifying Homogeneous and Interpretable Groups for Conformal Prediction Natalia Martinez Gil, Dhaval Patel, Chandra Reddy, Giri Ganapavarapu, Roman Vaculin, Jayant Kalagnanam

NeurIPS 2024 Tiny Time Mixers (TTMs): Fast Pre-Trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series Vijay Ekambaram, Arindam Jati, Pankaj Dayama, Sumanta Mukherjee, Nam H. Nguyen, Wesley M. Gifford, Chandra Reddy, Jayant Kalagnanam

ICLR 2023 A Time Series Is Worth 64 Words: Long-Term Forecasting with Transformers Yuqi Nie, Nam H Nguyen, Phanwadee Sinthong, Jayant Kalagnanam

AAAI 2023 AI Model Factory: Scaling AI for Industry 4.0 Applications Dhaval Patel, Shuxin Lin, Dhruv Shah, Srideepika Jayaraman, Joern Ploennigs, Anuradha Bhamidipati, Jayant Kalagnanam

AAAI 2022 AnomalyKiTS: Anomaly Detection Toolkit for Time Series Dhaval Patel, Giridhar Ganapavarapu, Srideepika Jayaraman, Shuxin Lin, Anuradha Bhamidipaty, Jayant Kalagnanam

AAAI 2022 Interpretable Clustering via Multi-Polytope Machines Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy

NeurIPSW 2021 Math Programming Based Reinforcement Learning for Multi-Echelon Inventory Management Pavithra Harsha, Ashish Jagmohan, Jayant Kalagnanam, Brian Quanz, Divya Singhvi

NeurIPS 2020 A Scalable MIP-Based Method for Learning Optimal Multivariate Decision Trees Haoran Zhu, Pavankumar Murali, Dzung Phan, Lam Nguyen, Jayant Kalagnanam

AAAI 2020 Delay-Adaptive Distributed Stochastic Optimization Zhaolin Ren, Zhengyuan Zhou, Linhai Qiu, Ajay Deshpande, Jayant Kalagnanam

IJCAI 2016 Change Detection Using Directional Statistics Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam

AAAI 2006 Improved Bounds for Computing Kemeny Rankings Vincent Conitzer, Andrew J. Davenport, Jayant Kalagnanam

AAAI 2004 A Computational Study of the Kemeny Rule for Preference Aggregation Andrew J. Davenport, Jayant Kalagnanam

IJCAI 2001 Achieving Budget-Balance with Vickrey-Based Payment Schemes in Exchanges David C. Parkes, Jayant Kalagnanam, Marta Eso

AAAI 1999 Using Neural Networks in Agent Teams to Speed up Solution Discovery for Hard Multi-Criteria Problems Shaun Gittens, Richard Goodwin, Jayant Kalagnanam, Sesh Murthy

IJCAI 1989 Learning to Diagnose by Doing Jayant Kalagnanam, Eswaran Subrahmanian

UAI 1988 A Comparison of Decision Analysis and Expert Rules for Sequential Diagnosis Jayant Kalagnanam, Max Henrion