Prithwish Chakraborty
IBM
57 Papers
157 Citations
Prithwish Chakraborty is an academic researcher from IBM. The author has contributed to research in topics: Computer science & Particle swarm optimization. The author has an hindex of 16, co-authored 49 publications. Previous affiliations of Prithwish Chakraborty include Virginia Tech & Hewlett-Packard.
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Papers
•Proceedings Article
Forecasting a Moving Target: Ensemble Models for ILI Case Count Predictions.
Prithwish Chakraborty,Pejman Khadivi,Bryan Lewis,Aravindan Mahendiran,Jiangzhuo Chen,Patrick Butler,Elaine O. Nsoesie,Sumiko R. Mekaru,John S. Brownstein,Madhav V. Marathe,Naren Ramakrishnan +10 more
- 01 Jan 2014
TL;DR: This paper presents a detailed prospective analysis on the generation of robust quantitative predictions about temporal trends of flu activity, using several surrogate data sources for 15 Latin American countries, and presents a novel matrix factorization approach using neighborhood embedding to predict flu case counts.
Discrete harmony search based expert model for epileptic seizure detection in electroencephalography
TL;DR: A novel scheme was presented to detect epileptic seizure activity with very fast and highest accuracy from background electro encephalogram (EEG) data recorded from epileptic and normal subjects and it is found that the detection rate is 100% accurate with same level of sensitivity and specificity.
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A framework for evaluating epidemic forecasts
Farzaneh Sadat Tabataba,Farzaneh Sadat Tabataba,Prithwish Chakraborty,Naren Ramakrishnan,Naren Ramakrishnan,Srinivasan Venkatramanan,Jiangzhuo Chen,Bryan Lewis,Madhav V. Marathe,Madhav V. Marathe +9 more
TL;DR: This paper presents an evaluation framework which allows for combining different features, error measures, and ranking schema to evaluate forecasts, and demonstrates the utility of the framework by evaluating six forecasting methods for predicting influenza in the United States.
Dynamic Poisson Autoregression for Influenza-Like-Illness Case Count Prediction
Zheng Wang,Prithwish Chakraborty,Sumiko R. Mekaru,John S. Brownstein,Jieping Ye,Naren Ramakrishnan +5 more
- 10 Aug 2015
TL;DR: This paper develops a dynamic Poisson autoregressive model with exogenous inputs variables (DPARX) for flu forecasting and applies this model and the corresponding learning method on historical ILI records for 15 countries around the world using a variety of syndromic surveillance data sources.
•Proceedings Article
Fine-grained photovoltaic output prediction using a Bayesian ensemble
Prithwish Chakraborty,Manish Marwah,Martin Arlitt,Naren Ramakrishnan +3 more
- 22 Jul 2012
TL;DR: A novel Bayesian ensemble methodology involving three diverse predictors that captures the sequentiality implicit in PV generation and uses motifs mined from historical data to estimate the most likely mixture weights using a stream prediction methodology is described.