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ORCIDHarish G. Ramaswamy
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2020 – today
- 2024
[c16]P. Krishna Kumar, Harish G. Ramaswamy:
Graph Classification with GNNs: Optimisation, Representation & Inductive Bias. ECAI 2024: 2082-2089- [i14]Mahesh Lorik Yadav, Harish Guruprasad Ramaswamy, Chandrashekar Lakshminarayanan:
Half-Space Feature Learning in Neural Networks. CoRR abs/2404.04312 (2024) - [i13]P. Krishna Kumar, Harish G. Ramaswamy:
Graph Classification with GNNs: Optimisation, Representation and Inductive Bias. CoRR abs/2408.09266 (2024) - 2023
- [c15]Rahul Vashisht, Harish G. Ramaswamy:
On the Learning Dynamics of Attention Networks. ECAI 2023: 2394-2401 - [i12]Rahul Vashisht, Harish G. Ramaswamy:
On the Learning Dynamics of Attention Networks. CoRR abs/2307.13421 (2023) - 2022
- [c14]Lakshmi Narayan Pandey, Rahul Vashisht, Harish G. Ramaswamy:
On the Interpretability of Attention Networks. ACML 2022: 832-847 - [c13]Depen Morwani, Harish G. Ramaswamy:
Inductive Bias of Gradient Descent for Weight Normalized Smooth Homogeneous Neural Nets. ALT 2022: 827-880 - [i11]Harikrishna Narasimhan, Harish G. Ramaswamy, Shiv Kumar Tavker, Drona Khurana, Praneeth Netrapalli, Shivani Agarwal:
Consistent Multiclass Algorithms for Complex Metrics and Constraints. CoRR abs/2210.09695 (2022) - [i10]Lakshmi Narayan Pandey, Rahul Vashisht, Harish G. Ramaswamy:
On the Interpretability of Attention Networks. CoRR abs/2212.14776 (2022) - 2021
- [i9]Umangi Jain, Harish G. Ramaswamy:
Predicting the success of Gradient Descent for a particular Dataset-Architecture-Initialization (DAI). CoRR abs/2111.13075 (2021) - 2020
- [c12]Mingyuan Zhang, Harish Guruprasad Ramaswamy, Shivani Agarwal:
Convex Calibrated Surrogates for the Multi-Label F-Measure. ICML 2020: 11246-11255 - [c11]Shiv Kumar Tavker, Harish Guruprasad Ramaswamy, Harikrishna Narasimhan:
Consistent Plug-in Classifiers for Complex Objectives and Constraints. NeurIPS 2020 - [c10]Saurabh Desai, Harish G. Ramaswamy:
Ablation-CAM: Visual Explanations for Deep Convolutional Network via Gradient-free Localization. WACV 2020: 972-980 - [i8]Mingyuan Zhang, Harish G. Ramaswamy, Shivani Agarwal:
Convex Calibrated Surrogates for the Multi-Label F-Measure. CoRR abs/2009.07801 (2020) - [i7]Depen Morwani, Harish G. Ramaswamy:
Inductive Bias of Gradient Descent for Exponentially Weight Normalized Smooth Homogeneous Neural Nets. CoRR abs/2010.12909 (2020) - [i6]Depen Morwani, Rahul Vashisht, Harish G. Ramaswamy:
Using noise resilience for ranking generalization of deep neural networks. CoRR abs/2012.08854 (2020)
2010 – 2019
- 2019
- [c9]Siddhartha Arora, Mitesh M. Khapra, Harish G. Ramaswamy:
On Knowledge distillation from complex networks for response prediction. NAACL-HLT (1) 2019: 3813-3822 - 2018
- [c8]Anirban Laha, Saneem Ahmed Chemmengath, Priyanka Agrawal, Mitesh M. Khapra, Karthik Sankaranarayanan, Harish G. Ramaswamy:
On Controllable Sparse Alternatives to Softmax. NeurIPS 2018: 6423-6433 - [i5]Anirban Laha, Saneem A. Chemmengath, Priyanka Agrawal, Mitesh M. Khapra, Karthik Sankaranarayanan, Harish G. Ramaswamy:
On Controllable Sparse Alternatives to Softmax. CoRR abs/1810.11975 (2018) - 2016
- [j1]Harish G. Ramaswamy, Shivani Agarwal:
Convex Calibration Dimension for Multiclass Loss Matrices. J. Mach. Learn. Res. 17: 14:1-14:45 (2016) - [c7]Harikrishna Narasimhan, Weiwei Pan, Purushottam Kar, Pavlos Protopapas, Harish G. Ramaswamy:
Optimizing the Multiclass F-Measure via Biconcave Programming. ICDM 2016: 1101-1106 - [c6]Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari:
Mixture Proportion Estimation via Kernel Embeddings of Distributions. ICML 2016: 2052-2060 - [i4]Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari:
Mixture Proportion Estimation via Kernel Embedding of Distributions. CoRR abs/1603.02501 (2016) - 2015
- [c5]Harish G. Ramaswamy, Ambuj Tewari, Shivani Agarwal:
Convex Calibrated Surrogates for Hierarchical Classification. ICML 2015: 1852-1860 - [c4]Harikrishna Narasimhan, Harish G. Ramaswamy, Aadirupa Saha, Shivani Agarwal:
Consistent Multiclass Algorithms for Complex Performance Measures. ICML 2015: 2398-2407 - [i3]Harish G. Ramaswamy, Harikrishna Narasimhan, Shivani Agarwal:
Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics. CoRR abs/1501.00287 (2015) - [i2]Harish G. Ramaswamy, Ambuj Tewari, Shivani Agarwal:
Consistent Algorithms for Multiclass Classification with a Reject Option. CoRR abs/1505.04137 (2015) - 2014
- [c3]Harish G. Ramaswamy, Balaji Srinivasan Babu, Shivani Agarwal, Robert C. Williamson:
On the Consistency of Output Code Based Learning Algorithms for Multiclass Learning Problems. COLT 2014: 885-902 - [i1]Harish G. Ramaswamy, Shivani Agarwal:
Convex Calibration Dimension for Multiclass Loss Matrices. CoRR abs/1408.2764 (2014) - 2013
- [c2]Harish G. Ramaswamy, Shivani Agarwal, Ambuj Tewari:
Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses. NIPS 2013: 1475-1483 - 2012
- [c1]Harish G. Ramaswamy, Shivani Agarwal:
Classification Calibration Dimension for General Multiclass Losses. NIPS 2012: 2087-2095
Coauthor Index
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