conftrace_

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

8

7

12

6

16

9

25

48

45

60

94

150

295

436

675

803

1,010

944

1,346

1,352

463

'10

'15

'20

'25

Papers (including subtopics)

VLEU: a Method for Automatic Evaluation for Generalizability of Text-to-Image Models EMNLP 2024 VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models EMNLP 2024 Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation NeurIPS 2024 WateRF: Robust Watermarks in Radiance Fields for Protection of Copyrights CVPR 2024 Weak-eval-Strong: Evaluating and Eliciting Lateral Thinking of LLMs with Situation Puzzles NeurIPS 2024 Weight Conditioning for Smooth Optimization of Neural Networks ECCV 2024 Weight decay induces low-rank attention layers NeurIPS 2024 Weight-Sharing Regularization AISTATS 2024 WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking NeurIPS 2024 What does automatic differentiation compute for neural networks? ICLR 2024 What does guidance do? A fine-grained analysis in a simple setting NeurIPS 2024 What do Graph Neural Networks learn? Insights from Tropical Geometry NeurIPS 2024 What Makes Quantization for Large Language Model Hard? An Empirical Study from the Lens of Perturbation AAAI 2024 When and How to Grow? On Efficient Pre-training via Model Growth ACML 2024 When are dynamical systems learned from time series data statistically accurate? NeurIPS 2024 When to Grow? A Fitting Risk-Aware Policy for Layer Growing in Deep Neural Networks AAAI 2024 Where Am I From? Identifying Origin of LLM-generated Content EMNLP 2024 Where am I? Large Language Models Wandering between Semantics and Structures in Long Contexts EMNLP 2024 Where Do Large Learning Rates Lead Us? NeurIPS 2024 White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is? JMLR 2024 Why are Sensitive Functions Hard for Transformers? ACL 2024 Why Do We Need Weight Decay in Modern Deep Learning? NeurIPS 2024 Why is parameter averaging beneficial in SGD? An objective smoothing perspective AISTATS 2024 Wide Two-Layer Networks can Learn from Adversarial Perturbations NeurIPS 2024 Wino Vidi Vici: Conquering Numerical Instability of 8-Bit Winograd Convolution for Accurate Inference Acceleration on Edge WACV 2024