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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
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules
NIPS 2022
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
NIPS 2022
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks
NIPS 2022
Sharpness-Aware Training for Free
NIPS 2022
Generalization Properties of NAS under Activation and Skip Connection Search
NIPS 2022
A Fast Post-Training Pruning Framework for Transformers
NIPS 2022
Exact Solutions of a Deep Linear Network
NIPS 2022
Deep Active Learning by Leveraging Training Dynamics
NIPS 2022
Benign Overfitting in Two-layer Convolutional Neural Networks
NIPS 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
NIPS 2022
Efficient Training of Low-Curvature Neural Networks
NIPS 2022
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks
NIPS 2022
Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent
NIPS 2022
The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
NIPS 2022
Does Momentum Change the Implicit Regularization on Separable Data?
NIPS 2022
Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution
NIPS 2022
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study
NIPS 2022
Is Integer Arithmetic Enough for Deep Learning Training?
NIPS 2022
A Reparametrization-Invariant Sharpness Measure Based on Information Geometry
NIPS 2022
Improving Transformer with an Admixture of Attention Heads
NIPS 2022
LTMD: Learning Improvement of Spiking Neural Networks with Learnable Thresholding Neurons and Moderate Dropout
NIPS 2022
Adam Can Converge Without Any Modification On Update Rules
NIPS 2022
M³ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design
NIPS 2022
Proppo: a Message Passing Framework for Customizable and Composable Learning Algorithms
NIPS 2022
Training stochastic stabilized supralinear networks by dynamics-neutral growth
NIPS 2022
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