Mahesh Subedar

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 19

Top Venues

Arizona State University, Tempe, USA (PHD)

Education History

Arizona State University, Tempe, USA

PHD

Publications

Athmanarayanan Lakshmi Narayanan, Ranganath Krishnan, Amrutha Machireddy, Mahesh Subedar
Parameter-Efficient Active Learning for Foundational models. CoRR (2024)
Jun-Liang Lin, Ranganath Krishnan, Keyur Ruganathbhai Ranipa, Mahesh Subedar, Vrushabh Sanghavi, Meena Arunachalam, Omesh Tickoo, Ravishankar Iyer, Mahmut Taylan Kandemir
Quantization for Bayesian Deep Learning: Low-Precision Characterization and Robustness. IISWC (2023)
Charles Hong, Qijing Huang, Grace Dinh, Mahesh Subedar, Yakun Sophia Shao
DOSA: Differentiable Model-Based One-Loop Search for DNN Accelerators. MICRO (2023)
Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo
Partially-Supervised Novel Object Captioning Using Context from Paired Data. BMVC (2022)
Qijing Huang, Charles Hong, John Wawrzynek, Mahesh Subedar, Yakun Sophia Shao
Learning A Continuous and Reconstructible Latent Space for Hardware Accelerator Design. ISPASS (2022)
Ranganath Krishnan, Alok Sinha, Nilesh Ahuja, Mahesh Subedar, Omesh Tickoo, Ravi Iyer
Mitigating Sampling Bias and Improving Robustness in Active Learning. CoRR (2021)
Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo
Data augmentation to improve robustness of image captioning solutions. CoRR (2021)
Ranganath Krishnan, Nilesh Ahuja, Alok Sinha, Mahesh Subedar, Omesh Tickoo, Ravi Iyer
Improving Robustness and Efficiency in Active Learning with Contrastive Loss. CoRR (2021)
Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo
Partially-supervised novel object captioning leveraging context from paired data. CoRR (2021)
Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes. AAAI (2020)
Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning. CoRR (2020)
Mahesh Subedar, Nilesh A. Ahuja, Ranganath Krishnan, Ibrahima J. Ndiour, Omesh Tickoo
Deep Probabilistic Models to Detect Data Poisoning Attacks. CoRR (2019)
Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang
Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference. CVPR Workshops (2019)
Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang
Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference. ICCV (2019)
Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
MOPED: Efficient priors for scalable variational inference in Bayesian deep neural networks. CoRR (2019)
Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
Efficient Priors for Scalable Variational Inference in Bayesian Deep Neural Networks. ICCV Workshops (2019)
Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo
BAR: Bayesian Activity Recognition using variational inference. CoRR (2018)
Mahesh Subedar, Ranganath Krishnan, Paulo Lopez-Meyer, Omesh Tickoo, Jonathan Huang
Uncertainty aware multimodal activity recognition with Bayesian inference. CoRR (2018)
Nilesh A. Ahuja, Mahesh Subedar, Omesh Tickoo, Yeongseon Lee
A Factorization Approach for Enabling Structure-from-Motion/SLAM Using Integer Arithmetic. ICCV Workshops (2017)
Mahesh Subedar, Lina J. Karam
Study of blur discrimination for 3D stereo viewing. SD&A (2014)
Abhijit Sarkar, Mark D. Fairchild, Jorge E. Caviedes, Mahesh Subedar
A Comparative Study of Color and Contrast Enhancement for Still Images and Consumer Video Applications. Color Imaging Conference (2008)
Mahesh Subedar, Lina J. Karam, Glen P. Abousleman
An embedded scaling-based arbitrary shape region-of-interest coding method for JPEG2000. ICASSP (3) (2004)
Mahesh Subedar, Lina J. Karam, Glen P. Abousleman
JPEG2000-based shape adaptive algorithm for the efficient coding of multiple regions-of interest. ICIP (2004)

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Publication Activity (10 Years)

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Mahesh Subedar