Jayant Kalagnanam

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 35

Top Topics

Integer Program

Anomaly Detection

Top Venues

Publications

Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam, Chandra Reddy
Multi-polytope Machine for Classification. SDM (2024)
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)
Vijay Ekambaram, Arindam Jati, Nam H. Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M. Gifford, Jayant Kalagnanam
Tiny Time Mixers (TTMs): Fast Pretrained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series. CoRR (2024)
Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers. ICLR (2023)
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 (2023)
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)
Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting. KDD (2023)
Vinícius Lima, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam
Optimal Control via Linearizable Deep Learning. ACC (2023)
Trang H. Tran, Lam M. Nguyen, Kyongmin Yeo, Nam Nguyen, Dzung Phan, Roman Vaculín, Jayant Kalagnanam
An End-to-End Time Series Model for Simultaneous Imputation and Forecast. CoRR (2023)
Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting. CoRR (2023)
Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy
Interpretable Clustering via Multi-Polytope Machines. AAAI (2022)
Dhaval Patel, Shuxin Lin, Jayant Kalagnanam
DSServe - Data Science using Serverless. Big Data (2022)
Dhaval Patel, Giridhar Ganapavarapu, Srideepika Jayaraman, Shuxin Lin, Anuradha Bhamidipaty, Jayant Kalagnanam
AnomalyKiTS: Anomaly Detection Toolkit for Time Series. AAAI (2022)
Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers. CoRR (2022)
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) (2022)
Srideepika Jayaraman, Chandra Reddy, Elham Khabiri, Dhaval Patel, Anuradha Bhamidipaty, Jayant Kalagnanam
Asset Modeling using Serverless Computing. IEEE BigData (2021)
Oktay Günlük, Jayant Kalagnanam, Minhan Li, Matt Menickelly, Katya Scheinberg
Optimal decision trees for categorical data via integer programming. J. Glob. Optim. 81 (1) (2021)
Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy
Interpretable Clustering via Multi-Polytope Machines. CoRR (2021)
Dhaval Patel, Shuxin Lin, Srideepika Jayaraman, Giridhar Ganapavarapu, Anuradha Bhamidipaty, Jayant Kalagnanam
Scaling Anomaly Detection Service Using Serverless Technology. IEEE BigData (2021)
Zhaonan Qu, Kaixiang Lin, Jayant Kalagnanam, Zhaojian Li, Jiayu Zhou, Zhengyuan Zhou
Federated Learning's Blessing: FedAvg has Linear Speedup. CoRR (2020)
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)
Zhaolin Ren, Zhengyuan Zhou, Linhai Qiu, Ajay Deshpande, Jayant Kalagnanam
Delay-Adaptive Distributed Stochastic Optimization. AAAI (2020)
Dhaval Patel, Nianjun Zhou, Shrey Shrivastava, Jayant Kalagnanam
Doctor for Machines: A Failure Pattern Analysis Solution for Industry 4.0. IEEE BigData (2020)
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)
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)
Arun Iyengar, Jayant Kalagnanam, Dhaval Patel, Chandra Reddy, Shrey Shrivastava
Providing Cooperative Data Analytics for Real Applications Using Machine Learning. ICDCS (2019)
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)
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)
Dhaval Patel, Lam M. Nguyen, Akshay Rangamani, Shrey Shrivastava, Jayant Kalagnanam
ChieF: A Change Pattern based Interpretable Failure Analyzer. IEEE BigData (2018)
Kyongmin Yeo, Youngdeok Hwang, Xiao Liu, Jayant Kalagnanam
Development of a spectral source inverse model by using generalized polynomial chaos. CoRR (2018)
Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam
Multi-task Multi-modal Models for Collective Anomaly Detection. ICDM (2017)
Dzung T. Phan, Tsuyoshi Idé, Jayant Kalagnanam, Matt Menickelly, Katya Scheinberg
A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization. ICDM Workshops (2017)
Matt Menickelly, Oktay Günlük, Jayant Kalagnanam, Katya Scheinberg
Optimal Generalized Decision Trees via Integer Programming. CoRR (2016)
Tsuyoshi Idé, Ankush Khandelwal, Jayant Kalagnanam
Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection. ICDM (2016)
Tsuyoshi Idé, Dzung T. Phan, Jayant Kalagnanam
Change Detection Using Directional Statistics. IJCAI (2016)
Kiran Kate, Sneha Chaudhari, Andy Prapanca, Jayant Kalagnanam
FoodSIS: a text mining system to improve the state of food safety in singapore. KDD (2014)
Kiran Kate, Andy Prapanca, Jayant Kalagnanam
InfoSuggest: A System for Automated Information Gathering: With a Real-World Case Study. SRII Global Conference (2014)
Kiran Kate, Sumit Negi, Jayant Kalagnanam
Monitoring Food Safety Violation Reports from Internet Forums. MIE (2014)
Jayant Kalagnanam, Max Henrion
A Comparison of Decision Analysis and Expert Rules for Sequential Diagnosis CoRR (2013)
Xue Bai, Manuel A. Nunez, Jayant Kalagnanam
Managing Data Quality Risk in Accounting Information Systems. Inf. Syst. Res. 23 (2) (2012)
Dzung T. Phan, Jayant Kalagnanam
Distributed methods for solving the security-constrained optimal power flow problem. ISGT (2012)
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)
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) (2011)
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) (2010)
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)
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) (2007)
Martin Bichler, Jayant Kalagnanam
A non-parametric estimator for setting reservation prices in procurement auctions. Inf. Technol. Manag. 7 (3) (2006)
Sugato Bagchi, Xue Bai, Jayant Kalagnanam
Data Quality Management using Business Process Modeling. IEEE SCC (2006)
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) (2006)
Vincent Conitzer, Andrew J. Davenport, Jayant Kalagnanam
Improved Bounds for Computing Kemeny Rankings. AAAI (2006)
Martin Bichler, Jayant Kalagnanam
Software frameworks for advanced procurement auction markets. Commun. ACM 49 (12) (2006)
Marta Eso, Soumyadip Ghosh, Jayant Kalagnanam, Laszlo Ladányi
Bid Evaluation in Procurement Auctions with Piecewise Linear Supply Curves. J. Heuristics 11 (2) (2005)
David C. Parkes, Jayant Kalagnanam
Models for Iterative Multiattribute Procurement Auctions. Manag. Sci. 51 (3) (2005)
Moninder Singh, Jayant Kalagnanam, Sudhir Verma, Amit J. Shah, Swaroop K. Chalasani
Automated cleansing for spend analytics. CIKM (2005)
Martin Bichler, Jayant Kalagnanam
Configurable offers and winner determination in multi-attribute auctions. Eur. J. Oper. Res. 160 (2) (2005)
Milind Dawande, Jayant Kalagnanam, Ho Soo Lee, Chandra Reddy, Stuart Siegel, Mark Trumbo
The Slab-Design Problem in the Steel Industry. Interfaces 34 (3) (2004)
Jayant Kalagnanam, Moninder Singh, Sudhir Verma, Michael Patek, Yuk Wah Wong
A system for automated mapping of bill-of-materials part numbers. KDD (2004)
Andrew J. Davenport, Jayant Kalagnanam
A Computational Study of the Kemeny Rule for Preference Aggregation. AAAI (2004)
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) (2004)
Liangzhao Zeng, Boualem Benatallah, Marlon Dumas, Jayant Kalagnanam, Quan Z. Sheng
Quality driven web services composition. WWW (2003)
Soumyadip Ghosh, Jayant Kalagnanam
Polyhedral sampling for multiattribute preference elicitation. EC (2003)
Liangzhao Zeng, Jun-Jang Jeng, Santhosh Kumaran, Jayant Kalagnanam
Reliable Execution Planning and Exception Handling for Business Process. TES (2003)
Martin Bichler, Jayant Kalagnanam
A nonoparametric estimator for setting: reserve prices in procurement auctions. EC (2003)
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) (2002)
F. Sibel Salman, Jayant Kalagnanam, Sesh Murthy, Andrew J. Davenport
Cooperative Strategies for Solving the Bicriteria Sparse Multiple Knapsack Problem. J. Heuristics 8 (2) (2002)
Martin Bichler, Jayant Kalagnanam, Ho Soo Lee, Juhnyoung Lee
Winner Determination Algorithms for Electronic Auctions: A Framework Design. EC-Web (2002)
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) (2001)
David C. Parkes, Jayant Kalagnanam, Marta Eso
Achieving Budget-Balance with Vickrey-Based Payment Schemes in Exchanges. IJCAI (2001)
Milind Dawande, Jayant Kalagnanam, Jay Sethuraman
Variable Sized Bin Packing With Color Constraints. Electron. Notes Discret. Math. 7 (2001)
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) (2000)
F. Sibel Salman, Jayant Kalagnanam, Sesh Murthy
Cooperative strategies for solving the bicriteria sparse multiple knapsack problem. CEC (1999)
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)
Jayant Kalagnanam, Urmila M. Diwekar
An optimization approach to order of magnitude reasoning. Artif. Intell. Eng. Des. Anal. Manuf. 8 (3) (1994)
Jayant Kalagnanam, Max Henrion, Eswaran Subrahmanian
The Scope of Dimensional Analysis in Qualitative Reasoning. Comput. Intell. 10 (1994)
Jayant Kalagnanam, Urmila M. Diwekar
An application of qualitative analysis of ordinary differential equations to azeotropic batch distillation. Artif. Intell. Eng. 8 (1) (1993)
Jayant Kalagnanam, Herbert A. Simon
Directions for Qualitative Reasoning. Comput. Intell. 8 (1992)
Jayant Kalagnanam, Herbert A. Simon, Yumi Iwasaki
The Mathematical Bases for Qualitative Reasoning. IEEE Expert 6 (2) (1991)
Jayant Kalagnanam, Eswaran Subrahmanian
Learning to Diagnose by Doing. IJCAI (1989)
Jayant Kalagnanam, Max Henrion
A comparison of decision alaysis and expert rules for sequential diagnosis. UAI (1988)