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Methodology
← Optimization & Theory
Machine Learning
›
Optimization & Theory
›
Neural Network Optimization
3648 directly classified 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 Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance
ICML 2021
Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
ICML 2021
Learning by Turning: Neural Architecture Aware Optimisation
ICML 2021
On Monotonic Linear Interpolation of Neural Network Parameters
ICML 2021
On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
ICML 2021
Implicit Regularization in Tensor Factorization
ICML 2021
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
ICML 2021
Nondeterminism and Instability in Neural Network Optimization
ICML 2021
A Modular Analysis of Provable Acceleration via Polyak’s Momentum: Training a Wide ReLU Network and a Deep Linear Network
ICML 2021
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
ICML 2021
Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
ICML 2021
Temporal Convolutional Network with Frequency Dimension Adaptive Attention for Speech Enhancement
INTERSPEECH 2021
Hierarchical Context-Aware Transformers for Non-Autoregressive Text to Speech
INTERSPEECH 2021
Large Norms of CNN Layers Do Not Hurt Adversarial Robustness
AAAI 2021
Going Deeper With Directly-Trained Larger Spiking Neural Networks
AAAI 2021
A Flexible Framework for Communication-Efficient Machine Learning
AAAI 2021
On the Adequacy of Untuned Warmup for Adaptive Optimization
AAAI 2021
A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization
AAAI 2021
Shuffling Recurrent Neural Networks
AAAI 2021
Training Spiking Neural Networks with Accumulated Spiking Flow
AAAI 2021
Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance
AAAI 2021
Reducing Neural Network Parameter Initialization Into an SMT Problem (Student Abstract)
AAAI 2021
Stability and Generalization of Decentralized Stochastic Gradient Descent
AAAI 2021
A Mixture-of-Experts Model for Antonym-Synonym Discrimination
ACL 2021
Gated Transformer for Robust De-noised Sequence-to-Sequence Modelling
EMNLP 2021
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