Research Explorer
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Achievements
About
Methodology
← Optimization & Theory
Deep Learning
›
Optimization & Theory
›
Optimization
1638 directly classified papers
Papers per year
2006: 5
2007: 2
2008: 4
2009: 2
2010: 2
2011: 3
2012: 8
2013: 25
2014: 19
2015: 22
2016: 31
2017: 42
2018: 68
2019: 104
2020: 148
2021: 174
2022: 178
2023: 209
2024: 345
2025: 244
2026: 3
Papers
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence
AAAI 2019
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI
AAAI 2019
How degenerate is the parametrization of neural networks with the ReLU activation function?
NIPS 2019
Deep Generalized Method of Moments for Instrumental Variable Analysis
NIPS 2019
A First-Order Algorithmic Framework for Distributionally Robust Logistic Regression
NIPS 2019
Ouroboros: On Accelerating Training of Transformer-Based Language Models
NIPS 2019
A Generic Acceleration Framework for Stochastic Composite Optimization
NIPS 2019
Sobolev Independence Criterion
NIPS 2019
Differentiable Convex Optimization Layers
NIPS 2019
Distributed Low-rank Matrix Factorization With Exact Consensus
NIPS 2019
A unified variance-reduced accelerated gradient method for convex optimization
NIPS 2019
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points
NIPS 2019
Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy Functions
NIPS 2019
Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning
NIPS 2019
RSN: Randomized Subspace Newton
NIPS 2019
Fine-grained Optimization of Deep Neural Networks
NIPS 2019
Dimension-Free Bounds for Low-Precision Training
NIPS 2019
Differentiable Ranking and Sorting using Optimal Transport
NIPS 2019
Surfing: Iterative Optimization Over Incrementally Trained Deep Networks
NIPS 2019
A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation
NIPS 2019
Massively scalable Sinkhorn distances via the Nyström method
NIPS 2019
Generalized Batch Normalization: Towards Accelerating Deep Neural Networks
AAAI 2019
Deep Neural Network Quantization via Layer-Wise Optimization Using Limited Training Data
AAAI 2019
TAPAS: Train-Less Accuracy Predictor for Architecture Search
AAAI 2019
Communication-Efficient Stochastic Gradient MCMC for Neural Networks
AAAI 2019
<
1
…
54
55
56
…
66
>