Harish G. Ramaswamy

According to our database1, Harish G. Ramaswamy authored at least 23 papers between 2012 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2023
On the Learning Dynamics of Attention Networks.
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.
CoRR, 2022

Inductive Bias of Gradient Descent for Weight Normalized Smooth Homogeneous Neural Nets.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

On the Interpretability of Attention Networks.
Proceedings of the Asian Conference on Machine Learning, 2022

2021
Predicting the success of Gradient Descent for a particular Dataset-Architecture-Initialization (DAI).
CoRR, 2021

2020
Using noise resilience for ranking generalization of deep neural networks.
CoRR, 2020

Inductive Bias of Gradient Descent for Exponentially Weight Normalized Smooth Homogeneous Neural Nets.
CoRR, 2020

Ablation-CAM: Visual Explanations for Deep Convolutional Network via Gradient-free Localization.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Consistent Plug-in Classifiers for Complex Objectives and Constraints.
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.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
On Knowledge distillation from complex networks for response prediction.
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.
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.
J. Mach. Learn. Res., 2016

Mixture Proportion Estimation via Kernel Embedding of Distributions.
CoRR, 2016

Mixture Proportion Estimation via Kernel Embeddings of Distributions.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Optimizing the Multiclass F-Measure via Biconcave Programming.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015
Consistent Algorithms for Multiclass Classification with a Reject Option.
CoRR, 2015

Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics.
CoRR, 2015

Convex Calibrated Surrogates for Hierarchical Classification.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Consistent Multiclass Algorithms for Complex Performance Measures.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
On the Consistency of Output Code Based Learning Algorithms for Multiclass Learning Problems.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses.
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.
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


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