Online Semi-infinite Linear Programming: Efficient Algorithms via Function Approximation
Online Semi-infinite Linear Programming: Efficient Algorithms via Function Approximation explores A novel approach to online semi-infinite linear programming that improves performance with function approximation.. Commercial viability score: 4/10 in Optimization Algorithms.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisConstrained Online Convex Optimization with Memory and PredictionsViability: 3.0
- Builds On ThisRegret Bounds for Competitive Resource Allocation with Endogenous CostsViability: 3.0
- Builds On ThisOffline Constrained RLHF with Multiple Preference OraclesViability: 3.0
- Builds On ThisOptimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPsViability: 2.0
- Builds On ThisA Perturbation Approach to Unconstrained Linear BanditsViability: 2.0