Optimization

Going Beyond Multi-Task Dense Prediction with Synergy Embedding Models CVPR 2024 GRaCE: Balancing Multiple Criteria to Achieve Stable, Collision-Free, and Functional Grasps RSS 2024 Gradient-Based Language Model Red Teaming EACL 2024 Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization ICML 2024 Gradient Consistency-based Parameter Allocation for Multilingual Neural Machine Translation COLING 2024 Gradient Coreset for Federated Learning WACV 2024 Gradient descent in matrix factorization: Understanding large initialization UAI 2024 Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization NeurIPS 2024 Gradient-free optimization of highly smooth functions: improved analysis and a new algorithm JMLR 2024 Gradient Guidance for Diffusion Models: An Optimization Perspective NeurIPS 2024 Gradient Methods for Online DR-Submodular Maximization with Stochastic Long-Term Constraints NeurIPS 2024 Gradients of Functions of Large Matrices NeurIPS 2024 Gradient-Variation Online Learning under Generalized Smoothness NeurIPS 2024 GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent AAAI 2024 Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization NeurIPS 2024 Gradual Optimization Learning for Conformational Energy Minimization ICLR 2024 Grammar-Aligned Decoding NeurIPS 2024 GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data ICLR 2024 Graph Bayesian Optimization for Multiplex Influence Maximization AAAI 2024 Graph Diffusion Policy Optimization NeurIPS 2024 Graph Edit Distance with General Costs Using Neural Set Divergence NeurIPS 2024 Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution NeurIPS 2024 Graph Geometry-Preserving Autoencoders ICML 2024 Graph Learning for Numeric Planning NeurIPS 2024 Graph Machine Learning through the Lens of Bilevel Optimization AISTATS 2024