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Found 5 papers, 2 papers with code
Introspective Tips: Large Language Model for In-Context Decision Making
The emergence of large language models (LLMs) has substantially influenced natural language processing, demonstrating exceptional results across various tasks.
Conservative State Value Estimation for Offline Reinforcement Learning
In this paper, we propose Conservative State Value Estimation (CSVE), a new approach that learns conservative V-function via directly imposing penalty on OOD states.
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
This paper investigates a critical resource allocation problem in the first party cloud: scheduling containers to machines.
A Surrogate Objective Framework for Prediction+Programming with Soft Constraints
Prediction+optimization is a common real-world paradigm where we have to predict problem parameters before solving the optimization problem.
A Surrogate Objective Framework for Prediction+Optimization with Soft Constraints
Prediction+optimization is a common real-world paradigm where we have to predict problem parameters before solving the optimization problem.
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