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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
Batch Normalization Alleviates the Spectral Bias in Coordinate Networks
CVPR 2024
ZeroRF: Fast Sparse View 360deg Reconstruction with Zero Pretraining
CVPR 2024
MLP Can Be A Good Transformer Learner
CVPR 2024
Passive Snapshot Coded Aperture Dual-Pixel RGB-D Imaging
CVPR 2024
SynSP: Synergy of Smoothness and Precision in Pose Sequences Refinement
CVPR 2024
Dual Prior Unfolding for Snapshot Compressive Imaging
CVPR 2024
A General and Efficient Training for Transformer via Token Expansion
CVPR 2024
AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurring
CVPR 2024
A Physics-informed Low-rank Deep Neural Network for Blind and Universal Lens Aberration Correction
CVPR 2024
Deep-TROJ: An Inference Stage Trojan Insertion Algorithm through Efficient Weight Replacement Attack
CVPR 2024
Towards Robust Learning to Optimize with Theoretical Guarantees
CVPR 2024
OrthCaps: An Orthogonal CapsNet with Sparse Attention Routing and Pruning
CVPR 2024
Sheared Backpropagation for Fine-tuning Foundation Models
CVPR 2024
Improved Implicit Neural Representation with Fourier Reparameterized Training
CVPR 2024
InceptionNeXt: When Inception Meets ConvNeXt
CVPR 2024
HIVE: Harnessing Human Feedback for Instructional Visual Editing
CVPR 2024
End-to-End Temporal Action Detection with 1B Parameters Across 1000 Frames
CVPR 2024
RepAn: Enhanced Annealing through Re-parameterization
CVPR 2024
Finding Lottery Tickets in Vision Models via Data-driven Spectral Foresight Pruning
CVPR 2024
Quantifying the Hyperparameter Sensitivity of Neural Networks for Character-level Sequence-to-Sequence Tasks
EACL 2024
Should I try multiple optimizers when fine-tuning a pre-trained Transformer for NLP tasks? Should I tune their hyperparameters?
EACL 2024
Over-Reasoning and Redundant Calculation of Large Language Models
EACL 2024
Extreme Fine-tuning: A Novel and Fast Fine-tuning Approach for Text Classification
EACL 2024
Dynamic Masking Rate Schedules for MLM Pretraining
EACL 2024
Personalized Abstractive Summarization by Tri-agent Generation Pipeline
EACL 2024
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