Harish G. Ramaswamy

According to our database, Harish G. Ramaswamy authored at least 27 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Impact of Label Noise on Learning Complex Features.

Rahul Vashisht, P. Krishna Kumar, Harsha Vardhan Govind, Harish G. Ramaswamy

CoRR, 2024

Graph Classification with GNNs: Optimisation, Representation and Inductive Bias.

P. Krishna Kumar, Harish G. Ramaswamy

CoRR, 2024

Half-Space Feature Learning in Neural Networks.

Mahesh Lorik Yadav, Harish Guruprasad Ramaswamy, Chandrashekar Lakshminarayanan

CoRR, 2024

Graph Classification with GNNs: Optimisation, Representation & Inductive Bias.

P. Krishna Kumar, Harish G. Ramaswamy

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

On the Learning Dynamics of Attention Networks.

Rahul Vashisht, Harish G. Ramaswamy

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022

Consistent Multiclass Algorithms for Complex Metrics and Constraints.

Harikrishna Narasimhan, Harish G. Ramaswamy, Shiv Kumar Tavker, Drona Khurana, Praneeth Netrapalli, Shivani Agarwal

CoRR, 2022

Inductive Bias of Gradient Descent for Weight Normalized Smooth Homogeneous Neural Nets.

Depen Morwani, Harish G. Ramaswamy

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

On the Interpretability of Attention Networks.

Lakshmi Narayan Pandey, Rahul Vashisht, Harish G. Ramaswamy

Proceedings of the Asian Conference on Machine Learning, 2022

2021

Predicting the success of Gradient Descent for a particular Dataset-Architecture-Initialization (DAI).

Umangi Jain, Harish G. Ramaswamy

CoRR, 2021

2020

Using noise resilience for ranking generalization of deep neural networks.

Depen Morwani, Rahul Vashisht, Harish G. Ramaswamy

CoRR, 2020

Inductive Bias of Gradient Descent for Exponentially Weight Normalized Smooth Homogeneous Neural Nets.

Depen Morwani, Harish G. Ramaswamy

CoRR, 2020

Ablation-CAM: Visual Explanations for Deep Convolutional Network via Gradient-free Localization.

Saurabh Desai, Harish G. Ramaswamy

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Consistent Plug-in Classifiers for Complex Objectives and Constraints.

Shiv Kumar Tavker, Harish Guruprasad Ramaswamy, Harikrishna Narasimhan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Convex Calibrated Surrogates for the Multi-Label F-Measure.

Mingyuan Zhang, Harish Guruprasad Ramaswamy, Shivani Agarwal

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

On Knowledge distillation from complex networks for response prediction.

Siddhartha Arora, Mitesh M. Khapra, Harish G. Ramaswamy

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

2018

On Controllable Sparse Alternatives to Softmax.

Anirban Laha, Saneem Ahmed Chemmengath, Priyanka Agrawal, Mitesh M. Khapra, Karthik Sankaranarayanan, Harish G. Ramaswamy

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Convex Calibration Dimension for Multiclass Loss Matrices.

Harish G. Ramaswamy, Shivani Agarwal

J. Mach. Learn. Res., 2016

Mixture Proportion Estimation via Kernel Embedding of Distributions.

Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari

CoRR, 2016

Mixture Proportion Estimation via Kernel Embeddings of Distributions.

Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari

Proceedings of the 33nd International Conference on Machine Learning, 2016

Optimizing the Multiclass F-Measure via Biconcave Programming.

Harikrishna Narasimhan, Weiwei Pan, Purushottam Kar, Pavlos Protopapas, Harish G. Ramaswamy

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015

Consistent Algorithms for Multiclass Classification with a Reject Option.

Harish G. Ramaswamy, Ambuj Tewari, Shivani Agarwal

CoRR, 2015

Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics.

Harish G. Ramaswamy, Harikrishna Narasimhan, Shivani Agarwal

CoRR, 2015

Convex Calibrated Surrogates for Hierarchical Classification.

Harish G. Ramaswamy, Ambuj Tewari, Shivani Agarwal

Proceedings of the 32nd International Conference on Machine Learning, 2015

Consistent Multiclass Algorithms for Complex Performance Measures.

Harikrishna Narasimhan, Harish G. Ramaswamy, Aadirupa Saha, Shivani Agarwal

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

On the Consistency of Output Code Based Learning Algorithms for Multiclass Learning Problems.

Harish G. Ramaswamy, Balaji Srinivasan Babu, Shivani Agarwal, Robert C. Williamson

Proceedings of The 27th Conference on Learning Theory, 2014

2013

Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses.

Harish G. Ramaswamy, Shivani Agarwal, Ambuj Tewari

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Classification Calibration Dimension for General Multiclass Losses.

Harish G. Ramaswamy, Shivani Agarwal

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012