Optimization

Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond ICML 2024 Efficient Algorithms for Non-gaussian Single Index Models with Generative Priors AAAI 2024 Efficient Algorithms for Sum-Of-Minimum Optimization ICML 2024 Efficient and Robust Long-Form Speech Recognition with Hybrid H3-Conformer Interspeech 2024 Efficient Asynchronous Federated Learning with Prospective Momentum Aggregation and Fine-Grained Correction AAAI 2024 Efficient Centroid-Linkage Clustering NeurIPS 2024 Efficient Conditional Diffusion Model with Probability Flow Sampling for Image Super-resolution AAAI 2024 Efficient Continual Finite-Sum Minimization ICLR 2024 Efficient Convex Algorithms for Universal Kernel Learning JMLR 2024 Efficient Dataset Distillation via Minimax Diffusion CVPR 2024 Efficient Detection of Long Consistent Cycles and its Application to Distributed Synchronization CVPR 2024 EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models ICLR 2024 Efficient Dynamic Hard Negative Sampling for Dialogue Selection ACL 2024 Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability NeurIPS 2024 Efficient Hyperparameter Optimization with Adaptive Fidelity Identification CVPR 2024 Efficient Integrators for Diffusion Generative Models ICLR 2024 Efficient Leverage Score Sampling for Tensor Train Decomposition NeurIPS 2024 Efficient Lifelong Model Evaluation in an Era of Rapid Progress NeurIPS 2024 Efficient LLM Comparative Assessment: A Product of Experts Framework for Pairwise Comparisons EMNLP 2024 Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization NeurIPS 2024 Efficient LLM Scheduling by Learning to Rank NeurIPS 2024 Efficient Low-Dimensional Compression of Overparameterized Models AISTATS 2024 Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits ICML 2024 Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing NeurIPS 2024 Efficient MAE Towards Large-Scale Vision Transformers WACV 2024