optimization problem

A Knapsack by Any Other Name: Presentation impacts LLM performance on NP-hard problems EMNLP 2025 Cauchy-Schwarz Regularizers ICLR 2025 Guiding Large Language Models in Modeling Optimization Problems via Question Partitioning IJCAI 2025 LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch ICLR 2025 Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent ICML 2025 NOMATTERXAI: Generating “No Matter What” Alterfactual Examples for Explaining Black-Box Text Classification Models AAAI 2025 Large Language Models Can Learn Representation in Natural Language ACL 2024 Leveraging Optimization for Adaptive Attacks on Image Watermarks ICLR 2024 Parsimonious Learning-Augmented Approximations for Dense Instances of NP-hard Problems ICML 2024 End-to-End Learning for Optimization via Constraint-Enforcing Approximators AAAI 2023 Equal Improvability: A New Fairness Notion Considering the Long-term Impact ICLR 2023 Online Platforms and the Fair Exposure Problem under Homophily AAAI 2023 TabLeak: Tabular Data Leakage in Federated Learning ICML 2023 Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten ICML 2023 Very Fast, Approximate Counterfactual Explanations for Decision Forests AAAI 2023 Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses NeurIPS 2022 FuseBot: RF-Visual Mechanical Search RSS 2022 OMLT: Optimization & Machine Learning Toolkit JMLR 2022 On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach NeurIPS 2022 The Perils of Learning Before Optimizing AAAI 2022 Defocus Map Estimation and Deblurring From a Single Dual-Pixel Image ICCV 2021 EvaLDA: Efficient Evasion Attacks Towards Latent Dirichlet Allocation AAAI 2021 Partitioned Learned Bloom Filters ICLR 2021 Adaptation Properties Allow Identification of Optimized Neural Codes NeurIPS 2020 Automatically Learning Compact Quality-aware Surrogates for Optimization Problems NeurIPS 2020