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ORCIDJayant Kalagnanam
Jayant R. Kalagnanam
Person information
- affiliation: Thomas J. Watson Research Center, Yorktown Heights, USA
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2020 – today
- 2024
[c51]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- [c50]Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam, Chandra Reddy:
Multi-polytope Machine for Classification. SDM 2024: 109-117 - [i15]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) - 2023
- [c49]Dhaval Patel, Shuxin Lin, Dhruv Shah, Srideepika Jayaraman, Joern Ploennigs, Anuradha Bhamidipati, Jayant Kalagnanam:
AI Model Factory: Scaling AI for Industry 4.0 Applications. AAAI 2023: 16467-16469 - [c48]Vinícius Lima, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam:
Optimal Control via Linearizable Deep Learning. ACC 2023: 100-105 - [c47]Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam:
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers. ICLR 2023 - [c46]Vijay Ekambaram
, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam:
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting. KDD 2023: 459-469 - [i14]Trang H. Tran, Lam M. Nguyen, Kyongmin Yeo, Nam Nguyen, Dzung T. Phan, Roman Vaculín, Jayant Kalagnanam:
An End-to-End Time Series Model for Simultaneous Imputation and Forecast. CoRR abs/2306.00778 (2023) - [i13]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) - [i12]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
- [j29]Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam:
Finite-sum smooth optimization with SARAH. Comput. Optim. Appl. 82(3): 561-593 (2022) - [j28]Zhimei Ren, Zhengyuan Zhou, Jayant R. Kalagnanam:
Batched Learning in Generalized Linear Contextual Bandits With General Decision Sets. IEEE Control. Syst. Lett. 6: 37-42 (2022) - [j27]Jayant Kalagnanam, Dzung T. Phan, Pavankumar Murali, Lam M. Nguyen, Nianjun Zhou, Dharmashankar Subramanian, Raju Pavuluri, Xiang Ma, Crystal Lui, Giovane Cesar Da Silva:
AI-Based Real-Time Site-Wide Optimization for Process Manufacturing. INFORMS J. Appl. Anal. 52(4): 363-378 (2022) - [c45]Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy:
Interpretable Clustering via Multi-Polytope Machines. AAAI 2022: 7309-7316 - [c44]Dhaval Patel, Giridhar Ganapavarapu, Srideepika Jayaraman, Shuxin Lin, Anuradha Bhamidipaty, Jayant Kalagnanam:
AnomalyKiTS: Anomaly Detection Toolkit for Time Series. AAAI 2022: 13209-13211 - [c43]Dhaval Patel, Shuxin Lin, Jayant Kalagnanam:
DSServe - Data Science using Serverless. IEEE Big Data 2022: 2343-2345 - [i11]Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam:
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers. CoRR abs/2211.14730 (2022) - 2021
- [j26]Oktay Günlük, Jayant Kalagnanam, Minhan Li, Matt Menickelly, Katya Scheinberg:
Optimal decision trees for categorical data via integer programming. J. Glob. Optim. 81(1): 233-260 (2021) - [j25]Kyongmin Yeo, Dylan E. C. Grullon, Fan-Keng Sun, Duane S. Boning, Jayant R. Kalagnanam:
Variational Inference Formulation for a Model-Free Simulation of a Dynamical System with Unknown Parameters by a Recurrent Neural Network. SIAM J. Sci. Comput. 43(2): A1305-A1335 (2021) - [c42]Zhimei Ren, Zhengyuan Zhou, Jayant R. Kalagnanam:
Batched Learning in Generalized Linear Contextual Bandits with General Decision Sets. ACC 2021: 4958-4963 - [c41]Dzung T. Phan, Lam M. Nguyen, Pavankumar Murali, Nhan H. Pham, Hongsheng Liu, Jayant R. Kalagnanam:
Regression Optimization for System-level Production Control. ACC 2021: 5023-5028 - [c40]Srideepika Jayaraman, Chandra Reddy, Elham Khabiri, Dhaval Patel, Anuradha Bhamidipaty, Jayant Kalagnanam:
Asset Modeling using Serverless Computing. IEEE BigData 2021: 4084-4090 - [c39]Dhaval Patel, Shuxin Lin, Srideepika Jayaraman, Giridhar Ganapavarapu, Anuradha Bhamidipaty, Jayant Kalagnanam:
Scaling Anomaly Detection Service Using Serverless Technology. IEEE BigData 2021: 5982-5984 - [i10]Pavithra Harsha, Ashish Jagmohan, Jayant R. Kalagnanam, Brian Quanz, Divya Singhvi:
Math Programming based Reinforcement Learning for Multi-Echelon Inventory Management. CoRR abs/2112.02215 (2021) - [i9]Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy:
Interpretable Clustering via Multi-Polytope Machines. CoRR abs/2112.05653 (2021) - 2020
- [c38]Zhaolin Ren, Zhengyuan Zhou, Linhai Qiu, Ajay Deshpande, Jayant Kalagnanam:
Delay-Adaptive Distributed Stochastic Optimization. AAAI 2020: 5503-5510 - [c37]Dhaval Patel, Shrey Shrivastava, Wesley M. Gifford, Stuart Siegel, Jayant Kalagnanam, Chandra Reddy:
Smart-ML: A System for Machine Learning Model Exploration using Pipeline Graph. IEEE BigData 2020: 1604-1613 - [c36]Dhaval Patel, Nianjun Zhou, Shrey Shrivastava, Jayant Kalagnanam:
Doctor for Machines: A Failure Pattern Analysis Solution for Industry 4.0. IEEE BigData 2020: 1614-1623 - [c35]Dhaval Patel, Syed Yousaf Shah, Nianjun Zhou, Shrey Shrivastava, Arun Iyengar, Anuradha Bhamidipaty, Jayant Kalagnanam:
FLOps: On Learning Important Time Series Features for Real-Valued Prediction. IEEE BigData 2020: 1624-1633 - [c34]Dzung T. Phan, Lam M. Nguyen, Nam H. Nguyen, Jayant R. Kalagnanam:
Pruning Deep Neural Networks with $\ell_{0}$-constrained Optimization. ICDM 2020: 1214-1219 - [c33]Haoran Zhu, Pavankumar Murali, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam:
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees. NeurIPS 2020 - [i8]Kyongmin Yeo, Dylan E. C. Grullon, Fan-Keng Sun, Duane S. Boning, Jayant R. Kalagnanam:
Variational inference formulation for a model-free simulation of a dynamical system with unknown parameters by a recurrent neural network. CoRR abs/2003.01184 (2020) - [i7]Zhaonan Qu, Kaixiang Lin, Jayant Kalagnanam, Zhaojian Li, Jiayu Zhou, Zhengyuan Zhou:
Federated Learning's Blessing: FedAvg has Linear Speedup. CoRR abs/2007.05690 (2020) - [i6]Haoran Zhu, Pavankumar Murali, Dzung T. Phan, Lam M. Nguyen, Jayant R. Kalagnanam:
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees. CoRR abs/2011.03375 (2020)
2010 – 2019
- 2019
- [c32]Shrey Shrivastava, Dhaval Patel, Anuradha Bhamidipaty, Wesley M. Gifford, Stuart A. Siegel, Venkata Sitaramagiridharganesh Ganapavarapu, Jayant R. Kalagnanam:
DQA: Scalable, Automated and Interactive Data Quality Advisor. IEEE BigData 2019: 2913-2922 - [c31]Arun Iyengar, Jayant Kalagnanam, Dhaval Patel, Chandra Reddy, Shrey Shrivastava:
Providing Cooperative Data Analytics for Real Applications Using Machine Learning. ICDCS 2019: 1878-1890 - [c30]Dharmashankar Subramanian, Pavankumar Murali, Nianjun Zhou, Xiang Ma, Giovane Cesar Da Silva, Raju Pavuluri, Jayant Kalagnanam:
A Prediction-Optimization Framework for Site-Wide Process Optimization. ICIOT 2019: 125-132 - [c29]Shrey Shrivastava, Dhaval Patel, Wesley M. Gifford, Stuart Siegel, Jayant Kalagnanam:
ThunderML: A Toolkit for Enabling AI/ML Models on Cloud for Industry 4.0. ICWS 2019: 163-180 - [i5]Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam:
Optimal Finite-Sum Smooth Non-Convex Optimization with SARAH. CoRR abs/1901.07648 (2019) - 2018
- [c28]Dhaval Patel, Lam M. Nguyen, Akshay Rangamani, Shrey Shrivastava, Jayant Kalagnanam:
ChieF: A Change Pattern based Interpretable Failure Analyzer. IEEE BigData 2018: 1978-1985 - [i4]Kyongmin Yeo, Youngdeok Hwang, Xiao Liu, Jayant Kalagnanam:
Development of a spectral source inverse model by using generalized polynomial chaos. CoRR abs/1801.03009 (2018) - [i3]Lam M. Nguyen, Nam H. Nguyen, Dzung T. Phan, Jayant R. Kalagnanam, Katya Scheinberg:
When Does Stochastic Gradient Algorithm Work Well? CoRR abs/1801.06159 (2018) - 2017
- [c27]Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam:
Multi-task Multi-modal Models for Collective Anomaly Detection. ICDM 2017: 177-186 - [c26]Dzung T. Phan, Tsuyoshi Idé, Jayant Kalagnanam, Matt Menickelly, Katya Scheinberg:
A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization. ICDM Workshops 2017: 830-833 - 2016
- [c25]Tsuyoshi Idé, Ankush Khandelwal, Jayant Kalagnanam:
Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection. ICDM 2016: 955-960 - [c24]Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam:
Change Detection Using Directional Statistics. IJCAI 2016: 1613-1619 - [i2]Matt Menickelly, Oktay Günlük, Jayant Kalagnanam, Katya Scheinberg:
Optimal Generalized Decision Trees via Integer Programming. CoRR abs/1612.03225 (2016) - 2014
- [c23]Kiran Kate, Sneha Chaudhari, Andy Prapanca, Jayant Kalagnanam:
FoodSIS: a text mining system to improve the state of food safety in singapore. KDD 2014: 1709-1718 - [c22]Kiran Kate, Sumit Negi, Jayant Kalagnanam:
Monitoring Food Safety Violation Reports from Internet Forums. MIE 2014: 1090-1094 - [c21]Kiran Kate, Andy Prapanca, Jayant Kalagnanam:
InfoSuggest: A System for Automated Information Gathering: With a Real-World Case Study. SRII Global Conference 2014: 203-212 - 2013
- [i1]Jayant Kalagnanam, Max Henrion:
A Comparison of Decision Analysis and Expert Rules for Sequential Diagnosis. CoRR abs/1304.2362 (2013) - 2012
- [j24]Xue Bai, Manuel A. Nunez, Jayant Kalagnanam:
Managing Data Quality Risk in Accounting Information Systems. Inf. Syst. Res. 23(2): 453-473 (2012) - [c20]Dzung T. Phan, Jayant Kalagnanam:
Distributed methods for solving the security-constrained optimal power flow problem. ISGT 2012: 1-7 - 2011
- [j23]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:
Analytics-driven asset management. IBM J. Res. Dev. 55(1): 13 (2011) - [c19]Vijay Arya, Deva P. Seetharam, Shivkumar Kalyanaraman, Kejitan Dontas, Christopher J. Pavlovski, Steve Hoy, Jayant R. Kalagnanam:
Phase identification in smart grids. SmartGridComm 2011: 25-30 - [c18]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:
Modeling and simulation of building energy performance for portfolios of public buildings. WSC 2011: 915-927 - 2010
- [j22]Colin Harrison, B. Eckman, R. Hamilton, Perry Hartswick, Jayant Kalagnanam, Jurij R. Paraszczak, P. Williams:
Foundations for Smarter Cities. IBM J. Res. Dev. 54(4): 1-16 (2010)
2000 – 2009
- 2009
- [c17]Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen:
Learning dynamic temporal graphs for oil-production equipment monitoring system. KDD 2009: 1225-1234 - 2007
- [j21]Sanjeeb Dash, Jayant Kalagnanam, Chandra Reddy, Sang Hwa Song:
Production design for plate products in the steel industry. IBM J. Res. Dev. 51(3/4): 345-362 (2007) - [c16]Andrew J. Davenport, Jayant Kalagnanam, Chandra Reddy, Stuart Siegel, John Hou:
An Application of Constraint Programming to Generating Detailed Operations Schedules for Steel Manufacturing. CP 2007: 64-76 - 2006
- [j20]Martin Bichler, Jayant Kalagnanam:
Software frameworks for advanced procurement auction markets. Commun. ACM 49(12): 104-108 (2006) - [j19]John J. H. Forrest, Jayant Kalagnanam, Laszlo Ladányi:
A Column-Generation Approach to the Multiple Knapsack Problem with Color Constraints. INFORMS J. Comput. 18(1): 129-134 (2006) - [j18]Martin Bichler, Jayant Kalagnanam:
A non-parametric estimator for setting reservation prices in procurement auctions. Inf. Technol. Manag. 7(3): 157-169 (2006) - [c15]Sugato Bagchi, Xue Bai, Jayant Kalagnanam:
Data Quality Management using Business Process Modeling. IEEE SCC 2006: 398-405 - [c14]Vincent Conitzer, Andrew J. Davenport, Jayant Kalagnanam:
Improved Bounds for Computing Kemeny Rankings. AAAI 2006: 620-626 - 2005
- [j17]Martin Bichler, Jayant Kalagnanam:
Configurable offers and winner determination in multi-attribute auctions. Eur. J. Oper. Res. 160(2): 380-394 (2005) - [j16]Marta Eso, Soumyadip Ghosh, Jayant Kalagnanam, Laszlo Ladányi:
Bid Evaluation in Procurement Auctions with Piecewise Linear Supply Curves. J. Heuristics 11(2): 147-173 (2005) - [j15]David C. Parkes, Jayant Kalagnanam:
Models for Iterative Multiattribute Procurement Auctions. Manag. Sci. 51(3): 435-451 (2005) - [c13]Moninder Singh, Jayant Kalagnanam, Sudhir Verma, Amit J. Shah, Swaroop K. Chalasani:
Automated cleansing for spend analytics. CIKM 2005: 437-445 - 2004
- [j14]Milind Dawande, Jayant Kalagnanam, Ho Soo Lee, Chandra Reddy, Stuart Siegel, Mark Trumbo:
The Slab-Design Problem in the Steel Industry. Interfaces 34(3): 215-225 (2004) - [j13]Liangzhao Zeng, Boualem Benatallah, Anne H. H. Ngu, Marlon Dumas, Jayant Kalagnanam, Henry Chang:
QoS-Aware Middleware for Web Services Composition. IEEE Trans. Software Eng. 30(5): 311-327 (2004) - [c12]Andrew J. Davenport, Jayant Kalagnanam:
A Computational Study of the Kemeny Rule for Preference Aggregation. AAAI 2004: 697-702 - [c11]Jayant Kalagnanam, Moninder Singh, Sudhir Verma, Michael Patek, Yuk Wah Wong:
A system for automated mapping of bill-of-materials part numbers. KDD 2004: 805-810 - 2003
- [j12]Gail Hohner, John Rich, Ed Ng, Grant Reid, Andrew J. Davenport, Jayant R. Kalagnanam, Ho Soo Lee, Chae An:
Special Issue: 2002 Franz Edelman Award for Achievement in Operations Research and the Management Sciences: Combinatorial and Quantity-Discount Procurement Auctions Benefit Mars, Incorporated and Its Suppliers. Interfaces 33(1): 23-35 (2003) - [c10]Martin Bichler, Jayant Kalagnanam:
A nonoparametric estimator for setting: reserve prices in procurement auctions. EC 2003: 254-255 - [c9]Soumyadip Ghosh, Jayant Kalagnanam:
Polyhedral sampling for multiattribute preference elicitation. EC 2003: 256-257 - [c8]Liangzhao Zeng, Jun-Jang Jeng, Santhosh Kumaran, Jayant Kalagnanam:
Reliable Execution Planning and Exception Handling for Business Process. TES 2003: 119-130 - [c7]Liangzhao Zeng, Boualem Benatallah, Marlon Dumas, Jayant Kalagnanam, Quan Z. Sheng:
Quality driven web services composition. WWW 2003: 411-421 - 2002
- [j11]F. Sibel Salman, Jayant Kalagnanam, Sesh Murthy, Andrew J. Davenport:
Cooperative Strategies for Solving the Bicriteria Sparse Multiple Knapsack Problem. J. Heuristics 8(2): 215-239 (2002) - [j10]Martin Bichler, Jayant Kalagnanam, Kaan Katircioglu, Alan J. King, Richard D. Lawrence, Ho Soo Lee, Grace Y. Lin, Yingdong Lu:
Applications of flexible pricing in business-to-business electronic commerce. IBM Syst. J. 41(2): 287-302 (2002) - [c6]Martin Bichler, Jayant Kalagnanam, Ho Soo Lee, Juhnyoung Lee:
Winner Determination Algorithms for Electronic Auctions: A Framework Design. EC-Web 2002: 37-46 - 2001
- [j9]Jayant Kalagnanam, Andrew J. Davenport, Ho Soo Lee:
Computational Aspects of Clearing Continuous Call Double Auctions with Assignment Constraints and Indivisible Demand. Electron. Commer. Res. 1(3): 221-238 (2001) - [j8]Milind Dawande, Jayant Kalagnanam, Jay Sethuraman:
Variable Sized Bin Packing With Color Constraints. Electron. Notes Discret. Math. 7: 154-157 (2001) - [c5]David C. Parkes, Jayant Kalagnanam, Marta Eso:
Achieving Budget-Balance with Vickrey-Based Payment Schemes in Exchanges. IJCAI 2001: 1161-1168 - 2000
- [j7]Jayant R. Kalagnanam, Milind Dawande, Mark Trumbo, Ho Soo Lee:
The Surplus Inventory Matching Problem in the Process Industry. Oper. Res. 48(4): 505-516 (2000) - [j6]Milind Dawande, Jayant Kalagnanam, Pinar Keskinocak, F. Sibel Salman, R. Ravi:
Approximation Algorithms for the Multiple Knapsack Problem with Assignment Restrictions. J. Comb. Optim. 4(2): 171-186 (2000)
1990 – 1999
- 1999
- [c4]Shaun Gittens, Richard Goodwin, Jayant Kalagnanam, Sesh Murthy:
Using Neural Networks in Agent Teams to Speed Up Solution Discovery for Hard Multi-Criteria Problems. AAAI/IAAI 1999: 961 - [c3]F. Sibel Salman, Jayant Kalagnanam, Sesh Murthy:
Cooperative strategies for solving the bicriteria sparse multiple knapsack problem. CEC 1999: 53-60 - 1994
- [j5]Jayant Kalagnanam, Urmila M. Diwekar:
An optimization approach to order of magnitude reasoning. Artif. Intell. Eng. Des. Anal. Manuf. 8(3): 207-217 (1994) - [j4]Jayant Kalagnanam, Max Henrion, Eswaran Subrahmanian:
The Scope of Dimensional Analysis in Qualitative Reasoning. Comput. Intell. 10: 117-133 (1994) - 1993
- [j3]Jayant Kalagnanam, Urmila M. Diwekar:
An application of qualitative analysis of ordinary differential equations to azeotropic batch distillation. Artif. Intell. Eng. 8(1): 23-32 (1993) - 1992
- [j2]Jayant Kalagnanam, Herbert A. Simon:
Directions for Qualitative Reasoning. Comput. Intell. 8: 308-315 (1992) - 1991
- [j1]Jayant Kalagnanam, Herbert A. Simon, Yumi Iwasaki:
The Mathematical Bases for Qualitative Reasoning. IEEE Expert 6(2): 11-19 (1991)
1980 – 1989
- 1989
- [c2]Jayant Kalagnanam, Eswaran Subrahmanian:
Learning to Diagnose by Doing. IJCAI 1989: 556-561 - 1988
- [c1]Jayant Kalagnanam, Max Henrion:
A comparison of decision alaysis and expert rules for sequential diagnosis. UAI 1988: 271-282
Coauthor Index
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