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ORCIDSauptik Dhar
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2020 – today
- 2024
[j4]Sauptik Dhar
, Bernardo Gonzalez Torres:
DOC3: deep one class classification using contradictions. Mach. Learn. 113(8): 5109-5150 (2024)- 2021
- [j3]Sauptik Dhar, Junyao Guo, Jiayi (Jason) Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah:
A Survey of On-Device Machine Learning: An Algorithms and Learning Theory Perspective. ACM Trans. Internet Things 2(3): 15:1-15:49 (2021) - [i10]Sauptik Dhar, Bernardo Gonzalez Torres:
DOC3-Deep One Class Classification using Contradictions. CoRR abs/2105.07636 (2021) - [i9]Sauptik Dhar, Javad Heydari, Samarth Tripathi, Unmesh Kurup, Mohak Shah:
Evolving GANs: When Contradictions Turn into Compliance. CoRR abs/2106.09946 (2021) - [i8]Viswanath Ganapathy, Sauptik Dhar, Olimpiya Saha, Pelin Kurt Garberson, Javad Heydari, Mohak Shah:
A Survey on Proactive Customer Care: Enabling Science and Steps to Realize it. CoRR abs/2110.05015 (2021) - 2020
- [c10]Samarth Tripathi, Jiayi Liu, Sauptik Dhar, Unmesh Kurup, Mohak Shah:
Improving Model Training by Periodic Sampling over Weight Distributions. IEEE BigData 2020: 112-122 - [c9]Youngsuk Park, Sauptik Dhar, Stephen P. Boyd, Mohak Shah:
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize. ICASSP 2020: 3597-3601 - [i7]Sauptik Dhar, Unmesh Kurup, Mohak Shah:
Stabilizing Bi-Level Hyperparameter Optimization using Moreau-Yosida Regularization. CoRR abs/2007.13322 (2020)
2010 – 2019
- 2019
- [c8]Sauptik Dhar, Vladimir Cherkassky, Mohak Shah:
Multiclass Learning from Contradictions. NeurIPS 2019: 8398-8408 - [i6]Sauptik Dhar, Vladimir Cherkassky:
Single Class Universum-SVM. CoRR abs/1909.09862 (2019) - [i5]Youngsuk Park, Sauptik Dhar, Stephen P. Boyd, Mohak Shah:
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize. CoRR abs/1910.07056 (2019) - [i4]Sauptik Dhar, Junyao Guo, Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah:
On-Device Machine Learning: An Algorithms and Learning Theory Perspective. CoRR abs/1911.00623 (2019) - 2018
- [i3]Sauptik Dhar, Vladimir Cherkassky, Mohak Shah:
Multiclass Universum SVM. CoRR abs/1808.08111 (2018) - 2017
- [c7]Sauptik Dhar, Vladimir Cherkassky:
Universum learning for SVM regression. IJCNN 2017: 3641-3648 - 2016
- [i2]Sauptik Dhar, Vladimir Cherkassky:
Universum Learning for SVM Regression. CoRR abs/1605.08497 (2016) - [i1]Sauptik Dhar, Naveen Ramakrishnan, Vladimir Cherkassky, Mohak Shah:
Universum Learning for Multiclass SVM. CoRR abs/1609.09162 (2016) - 2015
- [j2]Sauptik Dhar, Vladimir Cherkassky:
Development and Evaluation of Cost-Sensitive Universum-SVM. IEEE Trans. Cybern. 45(4): 806-818 (2015) - [c6]Sauptik Dhar, Congrui Yi, Naveen Ramakrishnan, Mohak Shah:
ADMM based scalable machine learning on Spark. IEEE BigData 2015: 1174-1182 - [c5]Martha Ganser, Sauptik Dhar, Unmesh Kurup, Carlos Cunha, Aca Gacic:
A data-driven approach towards patient identification for telehealth programs. IEEE BigData 2015: 2551-2559 - [c4]Martha Ganser, Sauptik Dhar, Unmesh Kurup, Carlos Cunha, Aca Gacic:
Patient Identification for Telehealth Programs. ICMLA 2015: 360-363 - 2012
- [c3]Sauptik Dhar, Vladimir Cherkassky:
Cost-Sensitive Universum-SVM. ICMLA (1) 2012: 220-225 - 2011
- [j1]Vladimir Cherkassky, Sauptik Dhar, Wuyang Dai:
Practical Conditions for Effectiveness of the Universum Learning. IEEE Trans. Neural Networks 22(8): 1241-1255 (2011) - [c2]Sauptik Dhar, Vladimir Cherkassky:
Application of SOM to analysis of Minnesota soil survey data. IJCNN 2011: 633-639 - 2010
- [c1]Vladimir Cherkassky, Sauptik Dhar:
Simple Method for Interpretation of High-Dimensional Nonlinear SVM Classification Models. DMIN 2010: 267-272
Coauthor Index
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last updated on 2024-08-23 19:23 CEST by the dblp team
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