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cs.LG2025
Keep your distance: learning dispersed embeddings on
Evgeniia Tokarchuk, Hua Chang Bakker, Vlad Niculae
Learning well-separated features in high-dimensional spaces, such as text or image embeddings, is crucial for many machine learning applications. Achieving such separation can be e…
cs.LG2024
A Simpler Alternative to Variational Regularized Counterfactual Risk Minimization
Hua Chang Bakker, Shashank Gupta, Harrie Oosterhuis
Variance regularized counterfactual risk minimization (VRCRM) has been proposed as an alternative off-policy learning (OPL) method. VRCRM method uses a lower-bound on the -diver…