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Found 6 papers, 2 papers with code
From Large Language Models and Optimization to Decision Optimization CoPilot: A Research Manifesto
Significantly simplifying the creation of optimization models for real-world business problems has long been a major goal in applying mathematical optimization more widely to important business and societal decisions.
Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach
Accurate time series forecasting is critical for a wide range of problems with temporal data.
Reducing Air Pollution through Machine Learning
The predictive component of our framework employs various machine learning models, such as gradient-boosted tree-based models and ensemble methods, for time series forecasting.
oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions
Explicit engineering of reward functions for given environments has been a major hindrance to reinforcement learning methods.
Combating False Negatives in Adversarial Imitation Learning
In adversarial imitation learning, a discriminator is trained to differentiate agent episodes from expert demonstrations representing the desired behavior.
Avoidance Learning Using Observational Reinforcement Learning
We define avoidance learning as the process of optimizing the agent's reward while avoiding dangerous behaviors given by a demonstrator.
