Devansh Arpit
Devansh Arpit
Senior Research Scientist, Salesforce
Verified email at
TitleCited byYear
A closer look at memorization in deep networks
D Arpit, S Jastrzębski, N Ballas, D Krueger, E Bengio, MS Kanwal, ...
ICML 2017 (arXiv preprint arXiv:1706.05394), 2017
Three factors influencing minima in SGD
S Jastrzębski, Z Kenton, D Arpit, N Ballas, A Fischer, Y Bengio, A Storkey
ICANN 2018 (arXiv preprint arXiv:1711.04623), 2017
Normalization propagation: A parametric technique for removing internal covariate shift in deep networks
D Arpit, Y Zhou, BU Kota, V Govindaraju
ICML 2016 (arXiv preprint arXiv:1603.01431), 2016
Why regularized auto-encoders learn sparse representation?
D Arpit, Y Zhou, H Ngo, V Govindaraju
ICML 2016 (arXiv preprint arXiv:1505.05561), 2015
Residual connections encourage iterative inference
S Jastrzebski, D Arpit, N Ballas, V Verma, T Che, Y Bengio
ICLR 2018 (arXiv preprint arXiv:1710.04773), 2017
On the spectral bias of deep neural networks
N Rahaman, D Arpit, A Baratin, F Draxler, M Lin, FA Hamprecht, Y Bengio, ...
ICML 2019 (arXiv preprint arXiv:1806.08734), 2018
A walk with sgd
C Xing, D Arpit, C Tsirigotis, Y Bengio
arXiv preprint arXiv:1802.08770, 2018
Fraternal Dropout
K Zolna, D Arpit, D Suhubdy, Y Bengio
ICLR 2018 (arXiv preprint arXiv:1711.00066), 2017
Deep Nets Don't Learn via Memorization
D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ...
ICLR 2017 Workshop, 2017
Variational bi-lstms
S Shabanian, D Arpit, A Trischler, Y Bengio
arXiv preprint arXiv:1711.05717, 2017
Is joint training better for deep auto-encoders?
Y Zhou, D Arpit, I Nwogu, V Govindaraju
arXiv preprint arXiv:1405.1380, 2014
Locality-constrained low rank coding for face recognition
D Arpit, G Srivastava, Y Fu
Proceedings of the 21st International Conference on Pattern Recognition …, 2012
Fingerprint feature extraction from gray scale images by ridge tracing
D Arpit, A Namboodiri
2011 International Joint Conference on Biometrics (IJCB), 1-8, 2011
Dimensionality reduction with subspace structure preservation
D Arpit, I Nwogu, V Govindaraju
Advances in Neural Information Processing Systems, 712-720, 2014
An analysis of random projections in cancelable biometrics
D Arpit, I Nwogu, G Srivastava, V Govindaraju
arXiv preprint arXiv:1401.4489, 2014
Ridge Regression based classifiers for large scale class imbalanced datasets
D Arpit, S Wu, P Natarajan, R Prasad, P Natarajan
2013 IEEE Workshop on Applications of Computer Vision (WACV), 267-274, 2013
Person re-identification for improved multi-person multi-camera tracking by continuous entity association
N Narayan, N Sankaran, D Arpit, K Dantu, S Setlur, V Govindaraju
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
The Benefits of Over-parameterization at Initialization in Deep ReLU Networks
D Arpit, Y Bengio
arXiv preprint arXiv:1901.03611, 2019
h-detach: Modifying the LSTM Gradient Towards Better Optimization
D Arpit, B Kanuparthi, G Kerg, NR Ke, I Mitliagkas, Y Bengio
ICLR 2019 (arXiv preprint arXiv:1810.03023), 2018
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets
D Arpit, V Campos, Y Bengio
NeurIPs 2019, 2019
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