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Found 6 papers, 1 papers with code
A Research Framework for Understanding Education-Occupation Alignment with NLP Techniques
Understanding the gaps between job requirements and university curricula is crucial for improving student success and institutional effectiveness in higher education.
What Is Missing in IRM Training and Evaluation? Challenges and Solutions
We propose a new IRM variant to address this limitation based on a novel viewpoint of ensemble IRM games as consensus-constrained bi-level optimization.
Out-of-Distribution Detection in Dermatology using Input Perturbation and Subset Scanning
Current skin disease models could make incorrect inferences for test samples from different hardware devices and clinical settings or unknown disease samples, which are out-of-distribution (OOD) from the training samples.
Treatment Effect Estimation using Invariant Risk Minimization
Inferring causal individual treatment effect (ITE) from observational data is a challenging problem whose difficulty is exacerbated by the presence of treatment assignment bias.
Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration
To ensure that agents behave in ways aligned with the values of the societies in which they operate, we must develop techniques that allow these agents to not only maximize their reward in an environment, but also to learn and follow the implicit constraints of society.
Multi-Objective Reinforcement Learning
reinforcement-learning
Scalable Demand-Aware Recommendation
In particular for durable goods, time utility is a function of inter-purchase duration within product category because consumers are unlikely to purchase two items in the same category in close temporal succession.
