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)

AlterMOMA: Fusion Redundancy Pruning for Camera-LiDAR Fusion Models with Alternative Modality Masking NeurIPS 2024 A Model for Estimating the Economic Costs of Computer Vision Systems That Use Deep Learning AAAI 2024 A Multi-Level Framework for Accelerating Training Transformer Models ICLR 2024 An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness NeurIPS 2024 Analysing The Impact of Sequence Composition on Language Model Pre-Training ACL 2024 Analyzing and Improving the Training Dynamics of Diffusion Models CVPR 2024 Analyzing & Reducing the Need for Learning Rate Warmup in GPT Training NeurIPS 2024 An Analytic Solution to Covariance Propagation in Neural Networks AISTATS 2024 An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attention AAAI 2024 Anchor-based Large Language Models ACL 2024 An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations NeurIPS 2024 An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding NeurIPS 2024 An Empirical Study of Distributed Deep Learning Training on Edge (Student Abstract) AAAI 2024 An Empirical Study of Scaling Law for Scene Text Recognition CVPR 2024 An Empirical Study on Cross-lingual Vocabulary Adaptation for Efficient Language Model Inference EMNLP 2024 An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem NeurIPS 2024 Annotation alignment: Comparing LLM and human annotations of conversational safety EMNLP 2024 An operator preconditioning perspective on training in physics-informed machine learning ICLR 2024 A PDE-based Explanation of Extreme Numerical Sensitivities and Edge of Stability in Training Neural Networks JMLR 2024 A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners EMNLP 2024 A Phase Transition between Positional and Semantic Learning in a Solvable Model of Dot-Product Attention NeurIPS 2024 ApiQ: Finetuning of 2-Bit Quantized Large Language Model EMNLP 2024 Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient NeurIPS 2024 Approximation Rate of the Transformer Architecture for Sequence Modeling NeurIPS 2024 A provable control of sensitivity of neural networks through a direct parameterization of the overall bi-Lipschitzness NeurIPS 2024