Harish G. Ramaswamy

32 papers A* 6A 3B 1C 1Journal 17Unranked 4
YearRankTypeTitle / Venue / Authors
2025 — conf
Graph Representation of CTA Images for Spatially Aware Classification.
BIBM
P. Krishna Kumar, Harish G. Ramaswamy
2025 J jnl
Optimizing Shortfall Risk Metric for Learning Regression Models.
CoRR
Harish G. Ramaswamy, L. A. Prashanth
2024 J jnl
Consistent Multiclass Algorithms for Complex Metrics and Constraints.
J. Mach. Learn. Res.
Harikrishna Narasimhan, Harish G. Ramaswamy, Shiv Kumar Tavker, Drona Khurana, Praneeth Netrapalli, Shivani Agarwal
2024 A conf
Graph Classification with GNNs: Optimisation, Representation & Inductive Bias.
ECAI
P. Krishna Kumar, Harish G. Ramaswamy
2024 J jnl
Graph Classification with GNNs: Optimisation, Representation and Inductive Bias.
CoRR
P. Krishna Kumar, Harish G. Ramaswamy
2024 J jnl
Impact of Label Noise on Learning Complex Features.
CoRR
Rahul Vashisht, P. Krishna Kumar, Harsha Vardhan Govind, Harish G. Ramaswamy
2023 A conf
On the Learning Dynamics of Attention Networks.
ECAI
Rahul Vashisht, Harish G. Ramaswamy
2023 J jnl
On the Learning Dynamics of Attention Networks.
CoRR
Rahul Vashisht, Harish G. Ramaswamy
2022 J jnl
Consistent Multiclass Algorithms for Complex Metrics and Constraints.
CoRR
Harikrishna Narasimhan, Harish G. Ramaswamy, Shiv Kumar Tavker, Drona Khurana, Praneeth Netrapalli, Shivani Agarwal
2022 B conf
Inductive Bias of Gradient Descent for Weight Normalized Smooth Homogeneous Neural Nets.
ALT
Depen Morwani, Harish G. Ramaswamy
2022 C conf
On the Interpretability of Attention Networks.
ACML
Lakshmi Narayan Pandey, Rahul Vashisht, Harish G. Ramaswamy
2022 J jnl
On the Interpretability of Attention Networks.
CoRR
Lakshmi Narayan Pandey, Rahul Vashisht, Harish G. Ramaswamy
2021 J jnl
Predicting the success of Gradient Descent for a particular Dataset-Architecture-Initialization (DAI).
CoRR
Umangi Jain, Harish G. Ramaswamy
2020 A conf
Ablation-CAM: Visual Explanations for Deep Convolutional Network via Gradient-free Localization.
WACV
Saurabh Desai, Harish G. Ramaswamy
2020 J jnl
Convex Calibrated Surrogates for the Multi-Label F-Measure.
CoRR
Mingyuan Zhang, Harish G. Ramaswamy, Shivani Agarwal
2020 J jnl
Inductive Bias of Gradient Descent for Exponentially Weight Normalized Smooth Homogeneous Neural Nets.
CoRR
Depen Morwani, Harish G. Ramaswamy
2020 J jnl
Using noise resilience for ranking generalization of deep neural networks.
CoRR
Depen Morwani, Rahul Vashisht, Harish G. Ramaswamy
2019 — conf
On Knowledge distillation from complex networks for response prediction.
NAACL-HLT (1)
Siddhartha Arora, Mitesh M. Khapra, Harish G. Ramaswamy
2018 A* conf
On Controllable Sparse Alternatives to Softmax.
NeurIPS
Anirban Laha, Saneem Ahmed Chemmengath, Priyanka Agrawal, Mitesh M. Khapra, Karthik Sankaranarayanan, Harish G. Ramaswamy
2018 J jnl
On Controllable Sparse Alternatives to Softmax.
CoRR
Anirban Laha, Saneem A. Chemmengath, Priyanka Agrawal, Mitesh M. Khapra, Karthik Sankaranarayanan, Harish G. Ramaswamy
2016 J jnl
Convex Calibration Dimension for Multiclass Loss Matrices.
J. Mach. Learn. Res.
Harish G. Ramaswamy, Shivani Agarwal
2016 J jnl
Mixture Proportion Estimation via Kernel Embedding of Distributions.
CoRR
Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari
2016 A* conf
Mixture Proportion Estimation via Kernel Embeddings of Distributions.
ICML
Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari
2016 A* conf
Optimizing the Multiclass F-Measure via Biconcave Programming.
ICDM
Harikrishna Narasimhan, Weiwei Pan, Purushottam Kar, Pavlos Protopapas, Harish G. Ramaswamy
2015 J jnl
Consistent Algorithms for Multiclass Classification with a Reject Option.
CoRR
Harish G. Ramaswamy, Ambuj Tewari, Shivani Agarwal
2015 J jnl
Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics.
CoRR
Harish G. Ramaswamy, Harikrishna Narasimhan, Shivani Agarwal
2015 A* conf
Consistent Multiclass Algorithms for Complex Performance Measures.
ICML
Harikrishna Narasimhan, Harish G. Ramaswamy, Aadirupa Saha, Shivani Agarwal
2015 A* conf
Convex Calibrated Surrogates for Hierarchical Classification.
ICML
Harish G. Ramaswamy, Ambuj Tewari, Shivani Agarwal
2014 J jnl
Convex Calibration Dimension for Multiclass Loss Matrices.
CoRR
Harish G. Ramaswamy, Shivani Agarwal
2014 A* conf
On the Consistency of Output Code Based Learning Algorithms for Multiclass Learning Problems.
COLT
Harish G. Ramaswamy, Balaji Srinivasan Babu, Shivani Agarwal, Robert C. Williamson
2013 — conf
Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses.
NIPS
Harish G. Ramaswamy, Shivani Agarwal, Ambuj Tewari
2012 — conf
Classification Calibration Dimension for General Multiclass Losses.
NIPS
Harish G. Ramaswamy, Shivani Agarwal