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← Optimization & Theory
Machine Learning
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Optimization & Theory
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Neural Network Optimization
3,648 papers
Papers per year
2001: 1
2003: 1
2005: 2
2006: 3
2007: 6
2008: 1
2009: 7
2010: 5
2011: 7
2012: 9
2013: 17
2014: 18
2015: 40
2016: 76
2017: 113
2018: 214
2019: 324
2020: 414
2021: 489
2022: 445
2023: 524
2024: 469
2025: 386
2026: 77
Papers
A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization
AAAI 2021
DeepBlueAI at SemEval-2021 Task 7: Detecting and Rating Humor and Offense with Stacking Diverse Language Model-Based Methods
IJCNLP 2021
The Successful Ingredients of Policy Gradient Algorithms
IJCAI 2021
Faster Neural Network Training with Approximate Tensor Operations
NIPS 2021
Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity
ICML 2021
Reverse engineering learned optimizers reveals known and novel mechanisms
NIPS 2021
Layerwise Optimization by Gradient Decomposition for Continual Learning
CVPR 2021
Noise Stability Regularization for Improving BERT Fine-tuning
NAACL 2021
Generalization error bounds for deep unfolding RNNs
UAI 2021
A Universal Law of Robustness via Isoperimetry
NIPS 2021
Not All Operations Contribute Equally: Hierarchical Operation-Adaptive Predictor for Neural Architecture Search
ICCV 2021
Convergence and Alignment of Gradient Descent with Random Backpropagation Weights
NIPS 2021
Provable Memorization via Deep Neural Networks using Sub-linear Parameters
COLT 2021
A Modular Analysis of Provable Acceleration via Polyak’s Momentum: Training a Wide ReLU Network and a Deep Linear Network
ICML 2021
Stochastic Sign Descent Methods: New Algorithms and Better Theory
ICML 2021
Stability and Generalization of Decentralized Stochastic Gradient Descent
AAAI 2021
An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models
ACL 2021
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients
NIPS 2021
H-Transformer-1D: Fast One-Dimensional Hierarchical Attention for Sequences
ACL 2021
The future is log-Gaussian: ResNets and their infinite-depth-and-width limit at initialization
NIPS 2021
Shape Matters: Understanding the Implicit Bias of the Noise Covariance
COLT 2021
Convergence rates and approximation results for SGD and its continuous-time counterpart
COLT 2021
Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition
ICCV 2021
SKFAC: Training Neural Networks With Faster Kronecker-Factored Approximate Curvature
CVPR 2021
Generalized Spatio-Temporal RNN Beamformer for Target Speech Separation
INTERSPEECH 2021
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