← Optimization & Theory
Deep Learning › Optimization & Theory ›

Optimization

1638 directly classified papers

Papers per year

Papers

Optimized Gradient Clipping for Noisy Label Learning AAAI 2025
AdaDPCC: Adaptive Rate Control and Rate-Distortion-Complexity Optimization for Dynamic Point Cloud Compression AAAI 2025
Asymmetric Learning for Spectral Graph Neural Networks AAAI 2025
JAQ: Joint Efficient Architecture Design and Low-Bit Quantization with Hardware-Software Co-Exploration AAAI 2025
OTLRM: Orthogonal Learning-based Low-Rank Metric for Multi-Dimensional Inverse Problems AAAI 2025
Multi-Level Optimal Transport for Universal Cross-Tokenizer Knowledge Distillation on Language Models AAAI 2025
Adaptive Draft-Verification for Efficient Large Language Model Decoding AAAI 2025
Unleashing the Potential of Large Language Models as Prompt Optimizers: Analogical Analysis with Gradient-based Model Optimizers AAAI 2025
Faster Double Adaptive Gradient Methods AAAI 2025
Taming LLMs with Gradient Grouping ACL 2025
YuLan-Mini: Pushing the Limits of Open Data-efficient Language Model ACL 2025
Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training ACL 2025
LESA: Learnable LLM Layer Scaling-Up ACL 2025
QuZO: Quantized Zeroth-Order Fine-Tuning for Large Language Models EMNLP 2025
ProcrustesGPT: Compressing LLMs with Structured Matrices and Orthogonal Transformations ACL 2025
MUZO: Leveraging Multiple Queries and Momentum for Zeroth-Order Fine-Tuning of Large Language Models EMNLP 2025
DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models CVPR 2025
CoMMIT: Coordinated Multimodal Instruction Tuning EMNLP 2025
Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory CVPR 2025
Calibration Across Layers: Understanding Calibration Evolution in LLMs EMNLP 2025
Optimizing for the Shortest Path in Denoising Diffusion Model CVPR 2025
FLRC: Fine-grained Low-Rank Compressor for Efficient LLM Inference EMNLP 2025
Cascade Speculative Drafting for Even Faster LLM Inference NIPS 2024
Pre-trained Large Language Models Use Fourier Features to Compute Addition NIPS 2024
BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models NIPS 2024