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Ameya Prabhu

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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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Sampling Bias in Deep Active Classification: An Empirical Study

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

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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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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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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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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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Towards Sub-Word Level Compositions for Sentiment Analysis of Hindi-English Code Mixed Text

Nov 02, 2016
Ameya Prabhu, Aditya Joshi, Manish Shrivastava, Vasudeva Varma

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