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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
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization
NIPS 2016
SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques
NIPS 2016
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy
NIPS 2016
Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow
NIPS 2016
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
ICML 2016
Preconditioned Spectral Descent for Deep Learning
NIPS 2015
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
NIPS 2015
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
NIPS 2015
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
NIPS 2015
Spectral Representations for Convolutional Neural Networks
NIPS 2015
Training Very Deep Networks
NIPS 2015
Backpropagation for Energy-Efficient Neuromorphic Computing
NIPS 2015
\ell_1,p-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods
ICML 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
ICCV 2015
An Accelerated Proximal Coordinate Gradient Method
NIPS 2014
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)
NIPS 2013
Accelerating Stochastic Gradient Descent using Predictive Variance Reduction
NIPS 2013
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems
ICML 2013
Understanding Dropout
NIPS 2013
Stochastic Gradient Descent with Only One Projection
NIPS 2012
Learning optimal spike-based representations
NIPS 2012
Deep Learning Made Easier by Linear Transformations in Perceptrons
AISTATS 2012
Algorithms for Hyper-Parameter Optimization
NIPS 2011
Understanding the difficulty of training deep feedforward neural networks
AISTATS 2010
An analysis on negative curvature induced by singularity in multi-layer neural-network learning
NIPS 2010
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