Jayant Kalagnanam

92 papers A* 21A 8B 2C 1Misc 1Journal 44Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Embedding-based Synthetic Data Generation for Complex Reasoning Tasks. CoRR Srideepika Jayaraman, Achille Fokoue, Dhaval Patel, Jayant Kalagnanam
2026	J	`jnl`	Revisiting the Generic Transformer: Deconstructing a Strong Baseline for Time Series Foundation Models. CoRR Yunshi Wen, Wesley M. Gifford, Chandra Reddy, Lam M. Nguyen, Jayant Kalagnanam, Anak Agung Julius
2025	J	`jnl`	AssetOpsBench: Benchmarking AI Agents for Task Automation in Industrial Asset Operations and Maintenance. CoRR Dhaval Patel, Shuxin Lin, James T. Rayfield, Nianjun Zhou, Roman Vaculín, Natalia Martinez Gil, Fearghal O'Donncha, Jayant Kalagnanam
2025	A	`conf`	Convergence-Guaranteed Elastic Net Graphical Model Estimation with Applications to Anomaly Localization. SDM Dzung T. Phan, Matt Menickelly, Tsuyoshi Idé, Jayant Kalagnanam
2025	J	`jnl`	Deep Policy Iteration with Integer Programming for Inventory Management. Manuf. Serv. Oper. Manag. Pavithra Harsha, Ashish Jagmohan, Jayant Kalagnanam, Brian Quanz, Divya Singhvi
2025	J	`jnl`	FailureSensorIQ: A Multi-Choice QA Dataset for Understanding Sensor Relationships and Failure Modes. CoRR Christodoulos Constantinides, Dhaval Patel, Shuxin Lin, Claudio Guerrero, Sunil Dagajirao Patil, Jayant Kalagnanam
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`	QoS-Aware Service Composition: A Retrospective. IEEE Trans. Software Eng. Liangzhao Zeng, Boualem Benatallah, Marlon Dumas, Jayant Kalagnanam, Anne H. H. Ngu
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	J	`jnl`	Toward a Trustworthy Optimization Modeling Agent via Verifiable Synthetic Data Generation. CoRR Vinícius Lima, Dzung T. Phan, Jayant Kalagnanam, Dhaval Patel, Nianjun Zhou
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`	Identifying Homogeneous and Interpretable Groups for Conformal Prediction. UAI Natalia Martinez Gil, Dhaval Patel, Chandra Reddy, Giridhar Ganapavarapu, Roman Vaculín, Jayant Kalagnanam
2024	A	`conf`	Multi-polytope Machine for Classification. SDM Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam, Chandra Reddy
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
2023	A*	`conf`	A Time Series is Worth 64 Words: Long-term Forecasting with Transformers. ICLR Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
2023	A*	`conf`	AI Model Factory: Scaling AI for Industry 4.0 Applications. AAAI Dhaval Patel, Shuxin Lin, Dhruv Shah, Srideepika Jayaraman, Joern Ploennigs, Anuradha Bhamidipati, Jayant Kalagnanam
2023	J	`jnl`	An End-to-End Time Series Model for Simultaneous Imputation and Forecast. CoRR Trang H. Tran, Lam M. Nguyen, Kyongmin Yeo, Nam Nguyen, Dzung T. Phan, Roman Vaculín, Jayant Kalagnanam
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	C	`conf`	Optimal Control via Linearizable Deep Learning. ACC Vinícius Lima, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam
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	J	`jnl`	A Time Series is Worth 64 Words: Long-term Forecasting with Transformers. CoRR Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
2022	J	`jnl`	AI-Based Real-Time Site-Wide Optimization for Process Manufacturing. INFORMS J. Appl. Anal. Jayant Kalagnanam, Dzung T. Phan, Pavankumar Murali, Lam M. Nguyen, Nianjun Zhou, Dharmashankar Subramanian, Raju Pavuluri, Xiang Ma, Crystal Lui, Giovane Cesar Da Silva
2022	A*	`conf`	AnomalyKiTS: Anomaly Detection Toolkit for Time Series. AAAI Dhaval Patel, Giridhar Ganapavarapu, Srideepika Jayaraman, Shuxin Lin, Anuradha Bhamidipaty, Jayant Kalagnanam
2022	B	`conf`	DSServe - Data Science using Serverless. IEEE Big Data Dhaval Patel, Shuxin Lin, Jayant Kalagnanam
2022	A*	`conf`	Interpretable Clustering via Multi-Polytope Machines. AAAI Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy
2021	—	`conf`	Asset Modeling using Serverless Computing. IEEE BigData Srideepika Jayaraman, Chandra Reddy, Elham Khabiri, Dhaval Patel, Anuradha Bhamidipaty, Jayant Kalagnanam
2021	J	`jnl`	Interpretable Clustering via Multi-Polytope Machines. CoRR Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy
2021	J	`jnl`	Optimal decision trees for categorical data via integer programming. J. Glob. Optim. Oktay Günlük, Jayant Kalagnanam, Minhan Li, Matt Menickelly, Katya Scheinberg
2021	—	`conf`	Scaling Anomaly Detection Service Using Serverless Technology. IEEE BigData Dhaval Patel, Shuxin Lin, Srideepika Jayaraman, Giridhar Ganapavarapu, Anuradha Bhamidipaty, Jayant Kalagnanam
2020	A*	`conf`	A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees. NeurIPS Haoran Zhu, Pavankumar Murali, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam
2020	A*	`conf`	Delay-Adaptive Distributed Stochastic Optimization. AAAI Zhaolin Ren, Zhengyuan Zhou, Linhai Qiu, Ajay Deshpande, Jayant Kalagnanam
2020	—	`conf`	Doctor for Machines: A Failure Pattern Analysis Solution for Industry 4.0. IEEE BigData Dhaval Patel, Nianjun Zhou, Shrey Shrivastava, Jayant Kalagnanam
2020	—	`conf`	FLOps: On Learning Important Time Series Features for Real-Valued Prediction. IEEE BigData Dhaval Patel, Syed Yousaf Shah, Nianjun Zhou, Shrey Shrivastava, Arun Iyengar, Anuradha Bhamidipaty, Jayant Kalagnanam
2020	J	`jnl`	Federated Learning's Blessing: FedAvg has Linear Speedup. CoRR Zhaonan Qu, Kaixiang Lin, Jayant Kalagnanam, Zhaojian Li, Jiayu Zhou, Zhengyuan Zhou
2020	—	`conf`	Smart-ML: A System for Machine Learning Model Exploration using Pipeline Graph. IEEE BigData Dhaval Patel, Shrey Shrivastava, Wesley M. Gifford, Stuart Siegel, Jayant Kalagnanam, Chandra Reddy
2019	—	`conf`	A Prediction-Optimization Framework for Site-Wide Process Optimization. ICIOT Dharmashankar Subramanian, Pavankumar Murali, Nianjun Zhou, Xiang Ma, Giovane Cesar Da Silva, Raju Pavuluri, Jayant Kalagnanam
2019	A	`conf`	Providing Cooperative Data Analytics for Real Applications Using Machine Learning. ICDCS Arun Iyengar, Jayant Kalagnanam, Dhaval Patel, Chandra Reddy, Shrey Shrivastava
2019	A	`conf`	ThunderML: A Toolkit for Enabling AI/ML Models on Cloud for Industry 4.0. ICWS Shrey Shrivastava, Dhaval Patel, Wesley M. Gifford, Stuart Siegel, Jayant Kalagnanam
2018	—	`conf`	ChieF: A Change Pattern based Interpretable Failure Analyzer. IEEE BigData Dhaval Patel, Lam M. Nguyen, Akshay Rangamani, Shrey Shrivastava, Jayant Kalagnanam
2018	J	`jnl`	Development of a spectral source inverse model by using generalized polynomial chaos. CoRR Kyongmin Yeo, Youngdeok Hwang, Xiao Liu, Jayant Kalagnanam
2017	—	`conf`	A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization. ICDM Workshops Dzung T. Phan, Tsuyoshi Idé, Jayant Kalagnanam, Matt Menickelly, Katya Scheinberg
2017	A*	`conf`	Multi-task Multi-modal Models for Collective Anomaly Detection. ICDM Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam
2016	A*	`conf`	Change Detection Using Directional Statistics. IJCAI Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam
2016	J	`jnl`	Optimal Generalized Decision Trees via Integer Programming. CoRR Matt Menickelly, Oktay Günlük, Jayant Kalagnanam, Katya Scheinberg
2016	A*	`conf`	Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection. ICDM Tsuyoshi Idé, Ankush Khandelwal, Jayant Kalagnanam
2014	A*	`conf`	FoodSIS: a text mining system to improve the state of food safety in singapore. KDD Kiran Kate, Sneha Chaudhari, Andy Prapanca, Jayant Kalagnanam
2014	—	`conf`	InfoSuggest: A System for Automated Information Gathering: With a Real-World Case Study. SRII Global Conference Kiran Kate, Andy Prapanca, Jayant Kalagnanam
2014	—	`conf`	Monitoring Food Safety Violation Reports from Internet Forums. MIE Kiran Kate, Sumit Negi, Jayant Kalagnanam
2013	J	`jnl`	A Comparison of Decision Analysis and Expert Rules for Sequential Diagnosis CoRR Jayant Kalagnanam, Max Henrion
2012	—	`conf`	Distributed methods for solving the security-constrained optimal power flow problem. ISGT Dzung T. Phan, Jayant Kalagnanam
2012	J	`jnl`	Managing Data Quality Risk in Accounting Information Systems. Inf. Syst. Res. Xue Bai, Manuel A. Nunez, Jayant Kalagnanam
2011	J	`jnl`	Analytics-driven asset management. IBM J. Res. Dev. Arun Hampapur, H. Cao, Andrew J. Davenport, W. S. Dong, Don Fenhagen, Rogério Schmidt Feris, Germán S. Goldszmidt, Z. B. Jiang, Jayant Kalagnanam, Tarun Kumar, H. Li, Xuan Liu, Shilpa Mahatma, Sharath Pankanti, D. Pelleg, W. Sun, M. Taylor, Chunhua Tian, Segev Wasserkrug, Lexing Xie, Mujib Lodhi, C. Kiely, K. Butturff, L. Desjardins
2011	Misc	`conf`	Modeling and simulation of building energy performance for portfolios of public buildings. WSC Young M. Lee, Fei Liu, Lianjun An, Huijing Jiang, Chandra Reddy, Raya Horesh, Paul Nevill, Estepan Meliksetian, Pawan Chowdhary, Nat Mills, Young Tae Chae, Jane L. Snowdon, Jayant Kalagnanam, Joe Emberson, Al Paskevicous, Elliott Jeyaseelan, Robert Forest, Chris Cuthbert, Tony Cupido, Michael Bobker, Janine Belfast
2010	J	`jnl`	Foundations for Smarter Cities. IBM J. Res. Dev. Colin Harrison, B. Eckman, R. Hamilton, Perry Hartswick, Jayant Kalagnanam, Jurij R. Paraszczak, P. Williams
2007	A	`conf`	An Application of Constraint Programming to Generating Detailed Operations Schedules for Steel Manufacturing. CP Andrew J. Davenport, Jayant Kalagnanam, Chandra Reddy, Stuart Siegel, John Hou
2007	J	`jnl`	Production design for plate products in the steel industry. IBM J. Res. Dev. Sanjeeb Dash, Jayant Kalagnanam, Chandra Reddy, Sang Hwa Song
2006	J	`jnl`	A Column-Generation Approach to the Multiple Knapsack Problem with Color Constraints. INFORMS J. Comput. John J. H. Forrest, Jayant Kalagnanam, Laszlo Ladányi
2006	J	`jnl`	A non-parametric estimator for setting reservation prices in procurement auctions. Inf. Technol. Manag. Martin Bichler, Jayant Kalagnanam
2006	—	`conf`	Data Quality Management using Business Process Modeling. IEEE SCC Sugato Bagchi, Xue Bai, Jayant Kalagnanam
2006	A*	`conf`	Improved Bounds for Computing Kemeny Rankings. AAAI Vincent Conitzer, Andrew J. Davenport, Jayant Kalagnanam
2006	J	`jnl`	Software frameworks for advanced procurement auction markets. Commun. ACM Martin Bichler, Jayant Kalagnanam
2005	A	`conf`	Automated cleansing for spend analytics. CIKM Moninder Singh, Jayant Kalagnanam, Sudhir Verma, Amit J. Shah, Swaroop K. Chalasani
2005	J	`jnl`	Bid Evaluation in Procurement Auctions with Piecewise Linear Supply Curves. J. Heuristics Marta Eso, Soumyadip Ghosh, Jayant Kalagnanam, Laszlo Ladányi
2005	J	`jnl`	Configurable offers and winner determination in multi-attribute auctions. Eur. J. Oper. Res. Martin Bichler, Jayant Kalagnanam
2005	J	`jnl`	Models for Iterative Multiattribute Procurement Auctions. Manag. Sci. David C. Parkes, Jayant Kalagnanam
2004	A*	`conf`	A Computational Study of the Kemeny Rule for Preference Aggregation. AAAI Andrew J. Davenport, Jayant Kalagnanam
2004	A*	`conf`	A system for automated mapping of bill-of-materials part numbers. KDD Jayant Kalagnanam, Moninder Singh, Sudhir Verma, Michael Patek, Yuk Wah Wong
2004	J	`jnl`	QoS-Aware Middleware for Web Services Composition. IEEE Trans. Software Eng. Liangzhao Zeng, Boualem Benatallah, Anne H. H. Ngu, Marlon Dumas, Jayant Kalagnanam, Henry Chang
2004	J	`jnl`	The Slab-Design Problem in the Steel Industry. Interfaces Milind Dawande, Jayant Kalagnanam, Ho Soo Lee, Chandra Reddy, Stuart Siegel, Mark Trumbo
2003	A*	`conf`	A nonoparametric estimator for setting: reserve prices in procurement auctions. EC Martin Bichler, Jayant Kalagnanam
2003	A*	`conf`	Polyhedral sampling for multiattribute preference elicitation. EC Soumyadip Ghosh, Jayant Kalagnanam
2003	A*	`conf`	Quality driven web services composition. WWW Liangzhao Zeng, Boualem Benatallah, Marlon Dumas, Jayant Kalagnanam, Quan Z. Sheng
2003	—	`conf`	Reliable Execution Planning and Exception Handling for Business Process. TES Liangzhao Zeng, Jun-Jang Jeng, Santhosh Kumaran, Jayant Kalagnanam
2002	J	`jnl`	Applications of flexible pricing in business-to-business electronic commerce. IBM Syst. J. Martin Bichler, Jayant Kalagnanam, Kaan Katircioglu, Alan J. King, Richard D. Lawrence, Ho Soo Lee, Grace Y. Lin, Yingdong Lu
2002	J	`jnl`	Cooperative Strategies for Solving the Bicriteria Sparse Multiple Knapsack Problem. J. Heuristics F. Sibel Salman, Jayant Kalagnanam, Sesh Murthy, Andrew J. Davenport
2002	—	`conf`	Winner Determination Algorithms for Electronic Auctions: A Framework Design. EC-Web Martin Bichler, Jayant Kalagnanam, Ho Soo Lee, Juhnyoung Lee
2001	A*	`conf`	Achieving Budget-Balance with Vickrey-Based Payment Schemes in Exchanges. IJCAI David C. Parkes, Jayant Kalagnanam, Marta Eso
2001	J	`jnl`	Computational Aspects of Clearing Continuous Call Double Auctions with Assignment Constraints and Indivisible Demand. Electron. Commer. Res. Jayant Kalagnanam, Andrew J. Davenport, Ho Soo Lee
2001	J	`jnl`	Variable Sized Bin Packing With Color Constraints. Electron. Notes Discret. Math. Milind Dawande, Jayant Kalagnanam, Jay Sethuraman
2000	J	`jnl`	Approximation Algorithms for the Multiple Knapsack Problem with Assignment Restrictions. J. Comb. Optim. Milind Dawande, Jayant Kalagnanam, Pinar Keskinocak, F. Sibel Salman, R. Ravi
1999	B	`conf`	Cooperative strategies for solving the bicriteria sparse multiple knapsack problem. CEC F. Sibel Salman, Jayant Kalagnanam, Sesh Murthy
1999	—	`conf`	Using Neural Networks in Agent Teams to Speed Up Solution Discovery for Hard Multi-Criteria Problems. AAAI/IAAI Shaun Gittens, Richard Goodwin, Jayant Kalagnanam, Sesh Murthy
1994	J	`jnl`	An optimization approach to order of magnitude reasoning. Artif. Intell. Eng. Des. Anal. Manuf. Jayant Kalagnanam, Urmila M. Diwekar
1994	J	`jnl`	The Scope of Dimensional Analysis in Qualitative Reasoning. Comput. Intell. Jayant Kalagnanam, Max Henrion, Eswaran Subrahmanian
1993	J	`jnl`	An application of qualitative analysis of ordinary differential equations to azeotropic batch distillation. Artif. Intell. Eng. Jayant Kalagnanam, Urmila M. Diwekar
1992	J	`jnl`	Directions for Qualitative Reasoning. Comput. Intell. Jayant Kalagnanam, Herbert A. Simon
1991	J	`jnl`	The Mathematical Bases for Qualitative Reasoning. IEEE Expert Jayant Kalagnanam, Herbert A. Simon, Yumi Iwasaki
1989	A*	`conf`	Learning to Diagnose by Doing. IJCAI Jayant Kalagnanam, Eswaran Subrahmanian
1988	A	`conf`	A comparison of decision alaysis and expert rules for sequential diagnosis. UAI Jayant Kalagnanam, Max Henrion