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2021-09
Routine Bandits: Minimizing Regret on Recurring Problems
2021-08
Increased responsiveness to punishment of cocaine self-administration after experience with high punishment.
2021-07
Pharmacists' perceptions of a machine learning model for the identification of atypical medication orders.
Exploring polypharmacy with artificial intelligence: data analysis protocol.
2021-03
Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments.
2020-11
Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model.
2020-10
MICRA-Net: MICRoscopy Analysis Neural Network to solve detection, classification, and segmentation from a single simple auxiliary task
2020-07
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks
Deep interpretability for GWAS.
2020-06
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems
AISTATS 2020
(2020-06-03)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1910.04928 (2019-10-11)]2020-05
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well
2020-04
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract)
2019-09
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning
2019-07
Leveraging Observations in Bandits: Between Risks and Benefits
On-line Adaptative Curriculum Learning for GANs
2019-01
Leveraging exploration in off-policy algorithms via normalizing flows.
2018-11
Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis
Temporal Regularization in Markov Decision Process
2018-09
Machine Learning to Predict Osteoporotic Fracture Risk from Genotypes
2018-07
Leveraging Observational Learning for Exploration in Bandits
2018-01
Genomic Prediction of Osteoporosis Using 426,000 Individuals from UK Biobank
Temporal Regularization for Markov Decision Process
Streaming kernel regression with provably adaptive mean, variance, and regularization
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