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ORCIDPrateek Jaiswal
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2020 – today
- 2024
[j4]Prateek Jaiswal
, Jeffrey Larson:
Multistart algorithm for identifying all optima of nonconvex stochastic functions. Optim. Lett. 18(6): 1335-1360 (2024)- [j3]Prateek Jaiswal, Jeffrey Larson:
Correction: Multistart algorithm for identifying all optima of nonconvex stochastic functions. Optim. Lett. 18(7): 1755 (2024) - [c8]Prateek Jaiswal, Anoop Namboodiri:
Enhancing Face Quality Assessment through Age and Expression Analysis. ICVGIP 2024: 1:1-1:9 - 2023
- [j2]Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao:
Bayesian Joint Chance Constrained Optimization: Approximations and Statistical Consistency. SIAM J. Optim. 33(3): 1968-1995 (2023) - [c7]Prateek Jaiswal, Arka Koner, Anoop Namboodiri:
Advancing Fingerprint Recognition Quality Assessment: Introducing the FRBQ Metric for Enhanced Fingerprint Recognition. ICVGIP 2023: 18:1-18:9 - [c6]Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao:
On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making. NeurIPS 2023 - [i7]Prateek Jaiswal, Debdeep Pati, Anirban Bhattacharya, Bani K. Mallick:
Generalized Regret Analysis of Thompson Sampling using Fractional Posteriors. CoRR abs/2309.06349 (2023) - 2022
- [c5]Sudipta Banerjee, Prateek Jaiswal, Arun Ross:
Facial De-morphing: Extracting Component Faces from a Single Morph. IJCB 2022: 1-10 - [i6]Sudipta Banerjee, Prateek Jaiswal, Arun Ross:
Facial De-morphing: Extracting Component Faces from a Single Morph. CoRR abs/2209.02933 (2022) - 2021
- [i5]Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao:
Bayesian Joint Chance Constrained Optimization: Approximations and Statistical Consistency. CoRR abs/2106.12199 (2021) - 2020
- [j1]Prateek Jaiswal, Vinayak A. Rao, Harsha Honnappa:
Asymptotic Consistency of α-Rényi-Approximate Posteriors. J. Mach. Learn. Res. 21: 156:1-156:42 (2020) - [c4]Ruixin Wang, Prateek Jaiswal, Harsha Honnappa:
Estimating Stochastic Poisson Intensities Using Deep Latent Models. WSC 2020: 596-607 - [c3]Prateek Jaiswal, Harsha Honnappa:
Statistical Inference for Approximate Bayesian Optimal Design. WSC 2020: 2138-2148 - [i4]Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao:
Variational Bayesian Methods for Stochastically Constrained System Design Problems. CoRR abs/2001.01404 (2020) - [i3]Ruixin Wang, Prateek Jaiswal, Harsha Honnappa:
Estimating Stochastic Poisson Intensities Using Deep Latent Models. CoRR abs/2007.06037 (2020)
2010 – 2019
- 2019
- [c2]Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao:
Variational Bayesian Methods for Stochastically Constrained System Design Problems. AABI 2019: 1-12 - [i2]Prateek Jaiswal, Vinayak A. Rao, Harsha Honnappa:
Asymptotic Consistency of $α-$Rényi-Approximate Posteriors. CoRR abs/1902.01902 (2019) - [i1]Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao:
Asymptotic Consistency of Loss-Calibrated Variational Bayes. CoRR abs/1911.01288 (2019) - 2018
- [c1]Prateek Jaiswal, Harsha Honnappa, Raghu Pasupathy:
Optimal Allocations for sample Average Approximation. WSC 2018: 1874-1885
Coauthor Index
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