Optimization

Online Learning with Unknown Constraints ICML 2025 Online Linear Classification with Massart Noise ICML 2025 Online MDP with Prototypes Information: A Robust Adaptive Approach AAAI 2025 Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting AAAI 2025 Online Prompt Selection for Program Synthesis AAAI 2025 Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization ICLR 2025 On Mitigating Affinity Bias through Bandits with Evolving Biased Feedback ICML 2025 On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems AAAI 2025 On Probabilistic Embeddings in Optimal Dimension Reduction JMLR 2025 On Quantizing Neural Representation for Variable-Rate Video Coding ICLR 2025 On Speeding Up Language Model Evaluation ICLR 2025 On Stochastic Contextual Bandits with Knapsacks in Small Budget Regime ICLR 2025 On the Asymptotic Optimality of Confidence Interval Based Algorithms for Fixed Confidence MABs AAAI 2025 On the Convergence of Continual Federated Learning Using Incrementally Aggregated Gradients AISTATS 2025 On the Convergence of Projected Policy Gradient for Any Constant Step Sizes JMLR 2025 On the Crucial Role of Initialization for Matrix Factorization ICLR 2025 On the Duality between Gradient Transformations and Adapters ICML 2025 On the Hardness of Training Deep Neural Networks Discretely AAAI 2025 On the Inherent Privacy of Zeroth-Order Projected Gradient Descent AISTATS 2025 On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery ICLR 2025 On the Minimax Regret of Sequential Probability Assignment via Square-Root Entropy COLT 2025 On the Modelling of Constraints with Tractable Logical Operators AAAI 2025 On the Optimization Landscape of Low Rank Adaptation Methods for Large Language Models ICLR 2025 On the O(sqrt(d)/T^(1/4)) Convergence Rate of RMSProp and Its Momentum Extension Measured by l_1 Norm JMLR 2025 On the Privacy-preserving Generalized Eigenvalue Problem ACML 2025