Search Results for author: Udbhav Bamba

Found 6 papers, 4 papers with code

Partial Binarization of Neural Networks for Budget-Aware Efficient Learning

no code implementations12 Nov 2022 Udbhav Bamba, Neeraj Anand, Saksham Aggarwal, Dilip K. Prasad, Deepak K. Gupta

To address this issue, partial binarization techniques have been developed, but a systematic approach to mixing binary and full-precision parameters in a single network is still lacking.

Binarization Neural Network Compression +1

UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images

no code implementations25 Jun 2022 Deepak K. Gupta, Udbhav Bamba, Abhishek Thakur, Akash Gupta, Suraj Sharan, Ertugrul Demir, Dilip K. Prasad

Based on the outlined issues, we introduce a novel research problem of training CNN models for very large images, and present 'UltraMNIST dataset', a simple yet representative benchmark dataset for this task.

Semantic correspondence

Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learning

1 code implementation CVPR 2022 Arnav Chavan, Rishabh Tiwari, Udbhav Bamba, Deepak K. Gupta

MetaDOCK compresses the meta-model as well as the task-specific inner models, thus providing significant reduction in model size for each task, and through constraining the number of active kernels for every task, it implicitly mitigates the issue of meta-overfitting.

Meta-Learning

ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations

1 code implementation ICLR 2021 Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak K. Gupta

Structured pruning methods are among the effective strategies for extracting small resource-efficient convolutional neural networks from their dense counterparts with minimal loss in accuracy.

Rescaling CNN through Learnable Repetition of Network Parameters

1 code implementation14 Jan 2021 Arnav Chavan, Udbhav Bamba, Rishabh Tiwari, Deepak Gupta

We show that small base networks when rescaled, can provide performance comparable to deeper networks with as low as 6% of optimization parameters of the deeper one.

Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection

1 code implementation23 Mar 2020 Suyog Jadhav, Udbhav Bamba, Arnav Chavan, Rishabh Tiwari, Aryan Raj

Endoscopic artefact detection challenge consists of 1) Artefact detection, 2) Semantic segmentation, and 3) Out-of-sample generalisation.

object-detection Object Detection +2

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