Titlebook: Machine Learning and Knowledge Discovery in Databases: Research Track; European Conference, Danai Koutra,Claudia Plant,Francesco Bonchi Con

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Learning Distinct Features Helps, Provablyage .-distance between the hidden-layer features and theoretically investigate how learning non-redundant distinct features affects the performance of the network. To do so, we derive novel generalization bounds depending on feature diversity based on Rademacher complexity for such networks. Our ana

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: Fairness-Aware Graph Generative Adversarial Networksenhancing performance, with the issue of fairness remaining largely unexplored. Existing graph generation models prioritize minimizing graph reconstruction’s expected loss, which can result in representational disparities in the generated graphs that unfairly impact marginalized groups. This paper a

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spite of our increasingly detailed knowledge of the molecular alterations occurring in human tumors. In parallel, despite a growing number of clinical trials being conducted, the absolute number of drugs that are effective in humans is declining, and many new drugs move into the market without havi

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