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ORCIDSaketha Nath Jagarlapudi
Person information
- affiliation: Indian Institute of Technology Hyderabad, India
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2020 – today
- 2024
[j5]Piyushi Manupriya, Saketha Nath Jagarlapudi, Pratik Jawanpuria:
MMD-Regularized Unbalanced Optimal Transport. Trans. Mach. Learn. Res. 2024 (2024)- [c20]Piyushi Manupriya, Rachit Keerti Das, Sayantan Biswas, Saketha Nath Jagarlapudi:
Consistent Optimal Transport with Empirical Conditional Measures. AISTATS 2024: 3646-3654 - [c19]Piyushi Manupriya, Pratik Jawanpuria, Karthik S. Gurumoorthy, Saketha Nath Jagarlapudi, Bamdev Mishra:
Submodular framework for structured-sparse optimal transport. ICML 2024 - [i7]Piyushi Manupriya, Pratik Jawanpuria, Karthik S. Gurumoorthy, Saketha Nath Jagarlapudi, Bamdev Mishra:
Submodular Framework for Structured-Sparse Optimal Transport. CoRR abs/2406.04914 (2024) - 2023
- [i6]Piyushi Manupriya, Rachit Keerti Das, Sayantan Biswas, Shivam Chandhok, Saketha Nath Jagarlapudi:
Empirical Optimal Transport between Conditional Distributions. CoRR abs/2305.15901 (2023) - 2022
- [c18]Piyushi Manupriya, Tarun Ram Menta, Saketha Nath Jagarlapudi, Vineeth N. Balasubramanian:
Improving Attribution Methods by Learning Submodular Functions. AISTATS 2022: 2173-2190 - 2021
- [c17]Soumya Chatterjee, Ayush Maheshwari, Ganesh Ramakrishnan, Saketha Nath Jagarlapudi:
Joint Learning of Hyperbolic Label Embeddings for Hierarchical Multi-label Classification. EACL 2021: 2829-2841 - [i5]Soumya Chatterjee, Ayush Maheshwari, Ganesh Ramakrishnan, Saketha Nath Jagarlapudi:
Joint Learning of Hyperbolic Label Embeddings for Hierarchical Multi-label Classification. CoRR abs/2101.04997 (2021) - [i4]Piyushi Manupriya, Saketha Nath Jagarlapudi, Tarun Ram Menta, Vineeth N. Balasubramanian:
Improving Attribution Methods by Learning Submodular Functions. CoRR abs/2104.09073 (2021) - 2020
- [c16]Jagarlapudi Saketha Nath, Pratik Kumar Jawanpuria:
Statistical Optimal Transport posed as Learning Kernel Embedding. NeurIPS 2020 - [i3]J. Saketha Nath, Pratik Jawanpuria:
Statistical Optimal Transport posed as Learning Kernel Embedding. CoRR abs/2002.03179 (2020) - [i2]J. Saketha Nath:
Unbalanced Optimal Transport using Integral Probability Metric Regularization. CoRR abs/2011.05001 (2020)
2010 – 2019
- 2019
- [c15]Prafull Prakash, Chaitanya Murti, J. Saketha Nath, Chiranjib Bhattacharyya:
Optimizing DNN Architectures for High Speed Autonomous Navigation in GPS Denied Environments on Edge Devices. PRICAI (2) 2019: 468-481 - 2018
- [c14]Ayush Maheshwari, Vishwajeet Kumar, Ganesh Ramakrishnan, J. Saketha Nath:
Entity Resolution and Location Disambiguation in the Ancient Hindu Temples Domain using Web Data. NAACL-HLT (Demonstrations) 2018: 46-50 - 2016
- [c13]Arun Shankar Iyer, J. Saketha Nath, Sunita Sarawagi:
Privacy-preserving Class Ratio Estimation. KDD 2016: 925-934 - 2015
- [j4]Pratik Jawanpuria, Jagarlapudi Saketha Nath, Ganesh Ramakrishnan:
Generalized hierarchical kernel learning. J. Mach. Learn. Res. 16: 617-652 (2015) - 2014
- [c12]Pratik Jawanpuria, Manik Varma, J. Saketha Nath:
On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection. ICML 2014: 118-126 - [c11]Arun Shankar Iyer, J. Saketha Nath, Sunita Sarawagi:
Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection. ICML 2014: 530-538 - 2013
- [c10]Ankit Ramteke, Akshat Malu, Pushpak Bhattacharyya, J. Saketha Nath:
Detecting Turnarounds in Sentiment Analysis: Thwarting. ACL (2) 2013: 860-865 - 2012
- [c9]Pratik Jawanpuria, J. Saketha Nath:
A Convex Feature Learning Formulation for Latent Task Structure Discovery. ICML 2012 - [i1]Pratik Jawanpuria, J. Saketha Nath:
A Convex Feature Learning Formulation for Latent Task Structure Discovery. CoRR abs/1206.4611 (2012) - 2011
- [j3]Jonathan Aflalo, Aharon Ben-Tal, Chiranjib Bhattacharyya, Jagarlapudi Saketha Nath, Raman Sankaran:
Variable Sparsity Kernel Learning. J. Mach. Learn. Res. 12: 565-592 (2011) - [j2]Aharon Ben-Tal, Sahely Bhadra, Chiranjib Bhattacharyya, J. Saketha Nath:
Chance constrained uncertain classification via robust optimization. Math. Program. 127(1): 145-173 (2011) - [c8]Pratik Jawanpuria, Jagarlapudi Saketha Nath, Ganesh Ramakrishnan:
Efficient Rule Ensemble Learning using Hierarchical Kernels. ICML 2011: 161-168 - [c7]Pratik Jawanpuria, Jagarlapudi Saketha Nath:
Multi-task Multiple Kernel Learning. SDM 2011: 828-838
2000 – 2009
- 2009
- [c6]Jagarlapudi Saketha Nath, G. Dinesh, Raman Sankaran, Chiranjib Bhattacharyya, Aharon Ben-Tal, K. R. Ramakrishnan:
On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation. NIPS 2009: 844-852 - [c5]Sahely Bhadra, J. Saketha Nath, Aharon Ben-Tal, Chiranjib Bhattacharyya:
Interval Data Classification under Partial Information: A Chance-Constraint Approach. PAKDD 2009: 208-219 - 2007
- [c4]Rashmin Babaria, J. Saketha Nath, S. Krishnan, K. R. Sivaramakrishnan, Chiranjib Bhattacharyya, M. Narasimha Murty:
Focused crawling with scalable ordinal regression solvers. ICML 2007: 57-64 - [c3]J. Saketha Nath, Chiranjib Bhattacharyya:
Maximum Margin Classifiers with Specified False Positive and False Negative Error Rates. SDM 2007: 35-46 - 2006
- [j1]J. Saketha Nath, Shirish K. Shevade:
An efficient clustering scheme using support vector methods. Pattern Recognit. 39(8): 1473-1480 (2006) - [c2]J. Saketha Nath, Chiranjib Bhattacharyya, M. Narasimha Murty:
Clustering based large margin classification: a scalable approach using SOCP formulation. KDD 2006: 674-679 - 2005
- [c1]J. Saketha Nath, Shirish K. Shevade:
An Efficient Clustering Scheme using Support Vector Methods. IICAI 2005: 3436-3448
Coauthor Index
aka: Pratik Kumar Jawanpuria
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