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Identifying Interactions among Categorical Predictors with Monte-Carlo Tree Search
Identifying interpretable interactions among categorical predictors for predictive modeling is crucial in various research fields.
An Efficient Algorithm for Deep Stochastic Contextual Bandits
In this work, we formulate the SCB that uses a DNN reward function as a non-convex stochastic optimization problem, and design a stage-wise stochastic gradient descent algorithm to optimize the problem and determine the action policy.
Federated Nonconvex Sparse Learning
Nonconvex sparse learning plays an essential role in many areas, such as signal processing and deep network compression.
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