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Proximal policy optimization (PPO) is a reinforcement learning (RL) algorithm for training an intelligent agent. Specifically, it is a policy gradient method, often used for deep RL when the policy network is very large. The predecessor to PPO, Trust Region Policy Optimization (TRPO), was published in 2015.
Another alternative to RLHF called Direct Preference Optimization (DPO) has been proposed to learn human preferences. Like RLHF, it has been applied to align pre-trained large language models using human-generated preference data. Unlike RLHF, however, which first trains a separate intermediate model to understand what good outcomes look like ...
PPO. The Preferred Provider Organization plan is the most popular for those with employment-based insurance (currently 47% of them, in fact). PPOs allow the most flexibility in that people can ...
Unlike EPO members, however, PPO members are reimbursed for using medical care providers outside of their network of designated doctors and hospitals. However, when they use out-of-network providers PPO members are reimbursed at a reduced rate that may include higher deductibles and co-payments, lower reimbursement percentages, or a combination ...
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HMOs often provide preventive care for a lower copayment or for free, in order to keep members from developing a preventable condition that would require a great deal of medical services. When HMOs were coming into existence, indemnity plans often did not cover preventive services, such as immunizations , well-baby checkups , mammograms , or ...
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