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Data-driven Weight Initialization with Sylvester Solvers


May 02, 2021
Debasmit Das, Yash Bhalgat, Fatih Porikli

* Practical Machine Learning for Developing Countries Workshop, International Conference on Learning Representations, 2021 

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Structured Convolutions for Efficient Neural Network Design


Aug 06, 2020
Yash Bhalgat, Yizhe Zhang, Jamie Lin, Fatih Porikli


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LSQ+: Improving low-bit quantization through learnable offsets and better initialization


Apr 20, 2020
Yash Bhalgat, Jinwon Lee, Markus Nagel, Tijmen Blankevoort, Nojun Kwak

* Camera-ready for Joint Workshop on Efficient Deep Learning in Computer Vision, CVPR 2020 

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Learned Threshold Pruning


Feb 28, 2020
Kambiz Azarian, Yash Bhalgat, Jinwon Lee, Tijmen Blankevoort


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QKD: Quantization-aware Knowledge Distillation


Nov 28, 2019
Jangho Kim, Yash Bhalgat, Jinwon Lee, Chirag Patel, Nojun Kwak


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Teacher-Student Learning Paradigm for Tri-training: An Efficient Method for Unlabeled Data Exploitation


Sep 25, 2019
Yash Bhalgat, Zhe Liu, Pritam Gundecha, Jalal Mahmud, Amita Misra


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Annotation-cost Minimization for Medical Image Segmentation using Suggestive Mixed Supervision Fully Convolutional Networks


Dec 29, 2018
Yash Bhalgat, Meet Shah, Suyash Awate

* Medical Imaging meets NeurIPS 2018 Workshop 

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FusedLSTM: Fusing frame-level and video-level features for Content-based Video Relevance Prediction


Sep 29, 2018
Yash Bhalgat

* Submission report for the ACMMM CBVRP challenge 2018 

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Stamp processing with examplar features


Sep 16, 2016
Yash Bhalgat, Mandar Kulkarni, Shirish Karande, Sachin Lodha


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