Renato Cordeiro de Amorim
PulseAugur coverage of Renato Cordeiro de Amorim — every cluster mentioning Renato Cordeiro de Amorim across labs, papers, and developer communities, ranked by signal.
-
New VoICE framework enhances counterfactual explanations for feature-weighted clustering
Researchers have introduced VoICE, a novel framework for generating counterfactual explanations in feature-weighted k-means clustering. This method extends the concept of counterfactuals, typically used in supervised le…
-
New criterion optimizes k-means++ restarts using data difficulty
Researchers have developed a new criterion called GTRC for the k-means++ algorithm to determine the optimal number of restarts. This method uses a Good-Turing estimate and confidence bounds to dynamically adjust restart…
-
New Shapley-inspired k-means algorithm enhances feature weighting
Researchers have developed SHARK (Shapley Reweighted k-means), a novel feature-weighting method for clustering algorithms that avoids the need for additional hyperparameter tuning. This approach leverages Shapley values…
-
New CAFE method improves feature extraction using weighted k-means
Researchers have developed a new method called Cluster-Adaptive Feature Extraction (CAFE) that enhances unsupervised feature extraction. CAFE utilizes Minkowski weighted k-means ($mwk$-means) to adaptively weight featur…