Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions

NeurIPS 2010 Achintya KunduVikram TankasaliChiranjib BhattacharyyaAharon Ben-Tal

In this paper we consider the problem of learning an n x n Kernel matrix from m similarity matrices under general convex loss. Past research have extensively studied the m =1 case and have derived several algorithms which require sophisticated techniques like ACCP, SOCP, etc... (read more)

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