Optimization

Towards Fair Representation: Clustering and Consensus COLT 2025 Towards Foundation Models for Mixed Integer Linear Programming ICLR 2025 Towards hyperparameter-free optimization with differential privacy ICLR 2025 Towards Lifelong Model Editing via Simulating Ideal Editor ICML 2025 Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond ICML 2025 Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification JMLR 2025 Towards Optimal Evaluation Efficiency for Large Language Models EMNLP 2025 Towards Optimal Multi-draft Speculative Decoding ICLR 2025 Towards Precise Scaling Laws for Video Diffusion Transformers CVPR 2025 Towards Projected and Incremental Pseudo-Boolean Model Counting AAAI 2025 Towards Reward Fairness in RLHF: From a Resource Allocation Perspective ACL 2025 Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization ICLR 2025 Towards Robust Influence Functions with Flat Validation Minima ICML 2025 Towards Scalable and Deep Graph Neural Networks via Noise Masking AAAI 2025 Towards Scalable Topological Regularizers ICLR 2025 Towards Source-Free Machine Unlearning CVPR 2025 Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory CVPR 2025 Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models NAACL 2025 Towards the 30 by 30 Kunming-Montreal Global Biodiversity Framework Target: Optimising Graph Connectivity in Constraint-Based Spatial Planning IJCAI 2025 Towards Trustworthy, Efficient, and Scalable Machine Learning AAAI 2025 Towards Unbiased Information Extraction and Adaptation in Cross-Domain Recommendation AAAI 2025 Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis ICML 2025 TRACE-CS: A Synergistic Approach to Explainable Course Scheduling Using LLMs and Logic AAAI 2025 Tracking The Best Expert Privately ICML 2025 TRAIL: Trust-Aware Client Scheduling for Semi-Decentralized Federated Learning AAAI 2025