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On the interplay of network structure and gradient convergence in deep learning.

, , and . Allerton, page 488-495. IEEE, (2016)

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View variations effect in gait recognition and performance improvement using fusion., , , and . RAIT, page 892-896. IEEE, (2012)Convergence rates for pretraining and dropout: Guiding learning parameters using network structure., , and . CoRR, (2015)Robust Blind Deconvolution via Mirror Descent., , and . CoRR, (2018)Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty., , and . CoRR, (2018)On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging., , , , , and . IPMI, volume 11492 of Lecture Notes in Computer Science, page 99-111. Springer, (2019)Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization offers Significant Performance and Efficiency Gains., , , and . CoRR, (2019)Fuzzy based Pooling in Convolutional Neural Network for Image Classification., , , and . FUZZ-IEEE, page 1-6. IEEE, (2019)Prognosis of Diesel Engine (MBT) Using Feature Extraction Techniques: A Comparative Study., , , , and . ICPHM, page 1-6. IEEE, (2018)Online Graph Completion: Multivariate Signal Recovery in Computer Vision., , , , and . CoRR, (2020)FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret., , , and . ECCV (12), volume 12357 of Lecture Notes in Computer Science, page 365-381. Springer, (2020)