Delves into the curse of dimensionality in discrete optimization, highlighting the challenges of exponential computational time growth with problem size.
Explores the formulation and complexity of Support Vector Machines, including primal and dual forms, geometric interpretation, and algorithmic implications.
Explores breaking linear scaling relationships in catalysis through strategies like controlling ensembles, using ligands, and introducing complexities to enhance performance.
