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Found 8 papers, 1 papers with code
Making sense of violence risk predictions using clinical notes
Violence risk assessment in psychiatric institutions enables interventions to avoid violence incidents.
Machine Learning for Violence Risk Assessment Using Dutch Clinical Notes
We explore conventional and deep machine learning methods to assess violence risk in psychiatric patients using practitioner notes.
Automated Reinforcement Learning: An Overview
Automated RL provides a framework in which different components of RL including MDP modeling, algorithm selection and hyper-parameter optimization are modeled and defined automatically.
A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning
This paper proposes a Deep Reinforcement Learning (DRL) approach for solving knapsack problem.
Algorithms for slate bandits with non-separable reward functions
In this paper, we study a slate bandit problem where the function that determines the slate-level reward is non-separable: the optimal value of the function cannot be determined by learning the optimal action for each slot.
Towards Multi-perspective conformance checking with fuzzy sets
This affects the quality of the provided diagnostics, especially when there exists some tolerance with respect to reasonably small violations, and hampers the flexibility of the process.
Deep representation learning for individualized treatment effect estimation using electronic health records
We propose a novel hybrid model bridging multi-task deep learning and K-nearest neighbors (KNN) for ITE estimation.
Ranked #3 on
Causal Inference
on IHDP
Remaining Useful Lifetime Prediction via Deep Domain Adaptation
We propose a Domain Adversarial Neural Network (DANN) approach to learn domain-invariant features that can be used to predict the RUL in the target domain.
