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Optimization & Theory

7,804 papers (27 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (1,960) Model Compression (1,896) Efficient Computing (1,780) Theory (1,239) Neural Network Optimization (1,004) Evaluation (533) Regularization (177) Loss Functions (157) Interpretability (128) Stochastic Methods (119) Generalization (115) Sparse Optimization (25)

Papers per year

16
60
675
1,352
'10
'15
'20
'25

Papers (including subtopics)

RG-GAN: Dynamic Regenerative Pruning for Data-Efficient Generative Adversarial Networks AAAI 2024 Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications NeurIPS 2024 Robust Approximate Sampling via Stochastic Gradient Barker Dynamics AISTATS 2024 Robust Image Denoising through Adversarial Frequency Mixup CVPR 2024 Robustness-Guided Image Synthesis for Data-Free Quantization AAAI 2024 Robust Similarity Learning with Difference Alignment Regularization ICLR 2024 Robust Uncertainty Quantification Using Conformalised Monte Carlo Prediction AAAI 2024 RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization EMNLP 2024 S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity NeurIPS 2024 Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress? NeurIPS 2024 Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement CVPR 2024 SAM-PARSER: Fine-Tuning SAM Efficiently by Parameter Space Reconstruction AAAI 2024 SAMPa: Sharpness-aware Minimization Parallelized NeurIPS 2024 SasWOT: Real-Time Semantic Segmentation Architecture Search WithOut Training AAAI 2024 Scalable Data Ablation Approximations for Language Models through Modular Training and Merging EMNLP 2024 Scalable Efficient Training of Large Language Models with Low-dimensional Projected Attention EMNLP 2024 Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes NeurIPS 2024 Scalable Optimization in the Modular Norm NeurIPS 2024 ScaLearn: Simple and Highly Parameter-Efficient Task Transfer by Learning to Scale ACL 2024 Scaled Conjugate Gradient Method for Nonconvex Optimization in Deep Neural Networks JMLR 2024 Scaled Decoupled Distillation CVPR 2024 ScalingFilter: Assessing Data Quality through Inverse Utilization of Scaling Laws EMNLP 2024 Scaling Law for Time Series Forecasting NeurIPS 2024 Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large Language Models EMNLP 2024 Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations NeurIPS 2024