Följ
Abhisek Kundu
Abhisek Kundu
Research Scientist, Intel Parallel Computing Labs, India
Verifierad e-postadress på intel.com
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A study of BFLOAT16 for deep learning training
D Kalamkar, D Mudigere, N Mellempudi, D Das, K Banerjee, S Avancha, ...
arXiv preprint arXiv:1905.12322, 2019
2902019
Ternary neural networks with fine-grained quantization
N Mellempudi, A Kundu, D Mudigere, D Das, B Kaul, P Dubey
arXiv preprint arXiv:1705.01462, 2017
1272017
Mixed low-precision deep learning inference using dynamic fixed point
N Mellempudi, A Kundu, D Das, D Mudigere, B Kaul
arXiv preprint arXiv:1701.08978, 2017
282017
A note on randomized element-wise matrix sparsification
A Kundu, P Drineas
arXiv preprint arXiv:1404.0320, 2014
222014
Tensor processing primitives: A programming abstraction for efficiency and portability in deep learning workloads
E Georganas, D Kalamkar, S Avancha, M Adelman, C Anderson, A Breuer, ...
Proceedings of the International Conference for High Performance Computing …, 2021
192021
Incremental precision networks using residual inference and fine-grain quantization
A Kundu, N Mellempudi, D Mudigere, D Das
US Patent 11,556,772, 2023
172023
Recovering PCA and sparse PCA via hybrid-(l1, l2) sparse sampling of data elements
A Kundu, P Drineas, M Magdon-Ismail
Journal of Machine Learning Research 18 (75), 1-34, 2017
162017
Ternary residual networks
A Kundu, K Banerjee, N Mellempudi, D Mudigere, D Das, B Kaul, ...
arXiv preprint arXiv:1707.04679, 2017
142017
A study of BFLOAT16 for deep learning training (2019)
D Kalamkar, D Mudigere, N Mellempudi, D Das, K Banerjee, S Avancha, ...
arXiv preprint arXiv:1905.12322, 1905
121905
Multi-dimensional discovery of biomarker and phenotype complexes
PRO Payne, K Huang, K Keen-Circle, A Kundu, J Zhang, TB Borlawsky
BMC bioinformatics 11, 1-9, 2010
112010
A randomized rounding algorithm for sparse PCA
K Fountoulakis, A Kundu, EM Kontopoulou, P Drineas
ACM Transactions on Knowledge Discovery from Data (TKDD) 11 (3), 1-26, 2017
82017
A study of BFLOAT16 for deep learning training. arXiv 2019
D Kalamkar, D Mudigere, N Mellempudi, D Das, K Banerjee, S Avancha, ...
arXiv preprint arXiv:1905.12322, 2019
62019
Approximating sparse pca from incomplete data
A Kundu, P Drineas, M Magdon-Ismail
Advances in Neural Information Processing Systems 28, 2015
62015
A study of BFLOAT16 for deep learning training. arXiv
D Kalamkar, D Mudigere, N Mellempudi, D Das, K Banerjee, S Avancha, ...
arXiv preprint arXiv:1905.12322, 2019
52019
Ternary neural networks with fine-grained quantization. 2017
N Mellempudi, A Kundu, D Mudigere, D Das, B Kaul, P Dubey
arXiv preprint arxiv:1705.01462, 2017
52017
Synthesis of individual handwriting in bangla script
BB Chaudhuri, A Kundu
Proceedings of the ICFHR, 2008
52008
Measuring frequency and period separations in red-giant stars using machine learning
S Dhanpal, O Benomar, S Hanasoge, A Kundu, D Dhuri, D Das, B Kaul
The Astrophysical Journal 928 (2), 188, 2022
42022
K-tanh: Hardware efficient activations for deep learning
A Kundu, S Srinivasan, EC Qin, D Kalamkar, NK Mellempudi, D Das, ...
arXiv preprint arXiv:1909.07729, 2019
42019
Relaxed leverage sampling for low-rank matrix completion
A Kundu
Information Processing Letters 124, 6-9, 2017
32017
AUTOSPARSE: Towards Automated Sparse Training of Deep Neural Networks
A Kundu, NK Mellempudi, DT Vooturi, B Kaul, P Dubey
Workshop at International Conference on Learning Representation (ICLR 2023), 2023
22023
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Artiklar 1–20