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← Optimization & Theory
Deep Learning
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Optimization & Theory
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Neural Network Optimization
902 directly classified papers
Papers per year
2007: 1
2009: 1
2010: 2
2011: 1
2012: 3
2013: 4
2014: 1
2015: 9
2016: 14
2017: 20
2018: 30
2019: 66
2020: 127
2021: 106
2022: 117
2023: 106
2024: 190
2025: 100
2026: 4
Papers
On Implicit Filter Level Sparsity in Convolutional Neural Networks
CVPR 2019
Customizable Architecture Search for Semantic Segmentation
CVPR 2019
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron
AISTATS 2019
Towards a Better Understanding and Regularization of GAN Training Dynamics
UAI 2019
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search
CVPR 2019
Cascaded Projection: End-To-End Network Compression and Acceleration
CVPR 2019
Centripetal SGD for Pruning Very Deep Convolutional Networks With Complicated Structure
CVPR 2019
RENAS: Reinforced Evolutionary Neural Architecture Search
CVPR 2019
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
NIPS 2019
MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation
CVPR 2019
MnasNet: Platform-Aware Neural Architecture Search for Mobile
CVPR 2019
Understanding the Disharmony Between Dropout and Batch Normalization by Variance Shift
CVPR 2019
Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization
CVPR 2019
Regularizing Neural Networks via Stochastic Branch Layers
ACML 2019
Learning in the Machine: Random Backpropagation and the Deep Learning Channel (Extended Abstract)
IJCAI 2019
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
ICML 2019
Bayesian Learning of Neural Network Architectures
AISTATS 2019
Utilizing Class Information for Deep Network Representation Shaping
AAAI 2019
Learning Dynamic Generator Model by Alternating Back-Propagation through Time
AAAI 2019
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications
AAAI 2019
Calibrated Stochastic Gradient Descent for Convolutional Neural Networks
AAAI 2019
Continual and Multi-Task Architecture Search
ACL 2019
On the Continuity of Rotation Representations in Neural Networks
CVPR 2019
Iterative Residual Refinement for Joint Optical Flow and Occlusion Estimation
CVPR 2019
Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes
JMLR 2019
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