Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors a...
This paper identifies five distinct mechanisms by which a population-based algorithm might have an advantage over a solo-search algorithm in classical optimization. These mechanism...
Abstract--This paper proposes a unified optimization framework to solve the time parameterization problem of humanoid robot paths. Even though the time parameterization problem is ...
Recent results in complexity theory suggest that various economic theories require agents to solve computationally intractable problems. However, such results assume the agents ar...
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...