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Real-Time Evaluation in Online Continual Learning: A New Paradigm


Feb 02, 2023
Yasir Ghunaim, Adel Bibi, Kumail Alhamoud, Motasem Alfarra, Hasan Abed Al Kader Hammoud, Ameya Prabhu, Philip H. S. Torr, Bernard Ghanem

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Evaluating Inexact Unlearning Requires Revisiting Forgetting


Jan 17, 2022
Shashwat Goel, Ameya Prabhu, Ponnurangam Kumaraguru

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No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks


Apr 01, 2021
Shyamgopal Karthik, Ameya Prabhu, Puneet K. Dokania, Vineet Gandhi

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Simple Unsupervised Multi-Object Tracking


Jun 04, 2020
Shyamgopal Karthik, Ameya Prabhu, Vineet Gandhi

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"You might also like this model": Data Driven Approach for Recommending Deep Learning Models for Unknown Image Datasets


Nov 26, 2019
Ameya Prabhu, Riddhiman Dasgupta, Anush Sankaran, Srikanth Tamilselvam, Senthil Mani

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* NeurIPS 2019, New in ML Group 

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Sampling Bias in Deep Active Classification: An Empirical Study


Sep 20, 2019
Ameya Prabhu, Charles Dognin, Maneesh Singh

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* Accepted at EMNLP 2019 

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Deep Expander Networks: Efficient Deep Networks from Graph Theory


Jul 26, 2018
Ameya Prabhu, Girish Varma, Anoop Namboodiri

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* ECCV'18 

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Hybrid Binary Networks: Optimizing for Accuracy, Efficiency and Memory


Apr 11, 2018
Ameya Prabhu, Vishal Batchu, Rohit Gajawada, Sri Aurobindo Munagala, Anoop Namboodiri

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* Accepted in WACV'18 (Oral) 

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Distribution-Aware Binarization of Neural Networks for Sketch Recognition


Apr 09, 2018
Ameya Prabhu, Vishal Batchu, Sri Aurobindo Munagala, Rohit Gajawada, Anoop Namboodiri

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* Accepted at WACV '18 (Oral) 

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Towards Deep Learning in Hindi NER: An approach to tackle the Labelled Data Scarcity


Nov 16, 2016
Vinayak Athavale, Shreenivas Bharadwaj, Monik Pamecha, Ameya Prabhu, Manish Shrivastava

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* 7 pages 

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