Optimization

Towards Exact Gradient-based Training on Analog In-memory Computing NeurIPS 2024 Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters EMNLP 2024 Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations IJCAI 2024 Towards Large Certified Radius in Randomized Smoothing Using Quasiconcave Optimization AAAI 2024 Towards More Accurate Diffusion Model Acceleration with A Timestep Tuner CVPR 2024 Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers NeurIPS 2024 Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection ICLR 2024 Towards Scalable and Stable Parallelization of Nonlinear RNNs NeurIPS 2024 Towards Transferable Adversarial Attacks with Centralized Perturbation AAAI 2024 Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming NeurIPS 2024 Transcendence: Generative Models Can Outperform The Experts That Train Them NeurIPS 2024 Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and Flatness NeurIPS 2024 Tuning Stable Rank Shrinkage: Aiming at the Overlooked Structural Risk in Fine-tuning CVPR 2024 Understanding and Addressing the Under-Translation Problem from the Perspective of Decoding Objective ACL 2024 Understanding and Improving Optimization in Predictive Coding Networks AAAI 2024 Understanding Entropic Regularization in GANs JMLR 2024 Understanding Progressive Training Through the Framework of Randomized Coordinate Descent AISTATS 2024 Understanding Surprising Generalization Phenomena in Deep Learning AAAI 2024 UniPTS: A Unified Framework for Proficient Post-Training Sparsity CVPR 2024 Unlocking Black-Box Prompt Tuning Efficiency via Zeroth-Order Optimization EMNLP 2024 Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding ACL 2024 Unpacking Tokenization: Evaluating Text Compression and its Correlation with Model Performance ACL 2024 Untrained Neural Nets for Snapshot Compressive Imaging: Theory and Algorithms NeurIPS 2024 Unveiling the Lexical Sensitivity of LLMs: Combinatorial Optimization for Prompt Enhancement EMNLP 2024 VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models EMNLP 2024