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Visual Encoders for Data-Efficient Imitation Learning in Modern Video Games
Video games have served as useful benchmarks for the decision making community, but going beyond Atari games towards training agents in modern games has been prohibitively expensive for the vast majority of the research community.
Gradient-Boosted Based Structured and Unstructured Learning
Our proposed frameworks allow joint learning on both kinds of data by integrating the paradigms of boosting models and deep neural networks.
Multi-Layer Attention-Based Explainability via Transformers for Tabular Data
We propose a graph-oriented attention-based explainability method for tabular data.
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