combinatorial optimization
A type of optimization problem where the solution comprises discrete elements, often relevant in planning and resource allocation tasks in AI.
- $\texttt{STRCMP}$: Integrating Graph Structural Priors with Language Models for Combinatorial Optimization
- A Learning-Augmented Approach to Online Allocation Problems
- A Learning-Augmented Dynamic Programming Approach for Orienteering Problem with Time Windows
- Complexity Scaling Laws for Neural Models using Combinatorial Optimization
- Differentiable extensions with rounding guarantees for combinatorial optimization over permutations
- Explainable Reinforcement Learning from Human Feedback to Improve Alignment
- Foundations of Top-$k$ Decoding for Language Models
- Fractional Langevin Dynamics for Combinatorial Optimization via Polynomial-Time Escape
- Generation as Search Operator for Test-Time Scaling of Diffusion-based Combinatorial Optimization
- Geometric Algorithms for Neural Combinatorial Optimization with Constraints
- Hephaestus: Mixture Generative Modeling with Energy Guidance for Large-scale QoS Degradation
- Large Language Models as End-to-end Combinatorial Optimization Solvers
- MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
- ML4CO-Bench-101: Benchmark Machine Learning for Classic Combinatorial Problems on Graphs
- MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search
- NaDRO: Leveraging Dual-Reward Strategies for LLMs Training on Noisy Data
- Neural Rule Lists: Learning Discretizations, Rules, and Order in One Go
- OPTFM: A Scalable Multi-View Graph Transformer for Hierarchical Pre-Training in Combinatorial Optimization
- Oracle-Efficient Combinatorial Semi-Bandits
- PARCO: Parallel AutoRegressive Models for Multi-Agent Combinatorial Optimization
- ProDAG: Projected Variational Inference for Directed Acyclic Graphs
- Solving the Asymmetric Traveling Salesman Problem via Trace-Guided Cost Augmentation
- StruDiCO: Structured Denoising Diffusion with Gradient-free Inference-stage Boosting for Memory and Time Efficient Combinatorial Optimization
- Structured Reinforcement Learning for Combinatorial Decision-Making
- Towards Generalizable Multi-Policy Optimization with Self-Evolution for Job Scheduling