Patent Document ID: 8489524
Application ID: 13084692
Patent Flag: 1

Claim One:
1. A method to learn a classifier from a plurality of data batches, comprising: inputting a first data batch into a memory connected to a processor; learning a first support vector machine from the first data batch with the processor; the processor storing the first support vector machine in the memory; inputting a new data batch into the memory, the new data batch not being represented by the first data batch; and learning a new support vector machine by processing the first support vector machine and the new data batch and not the first data batch with the processor, including determining the new support vector machine by optimizing a function α ^ 𝒩 = argmin α 𝒩 ⁡ ( λ 2 ⁢ α 𝒩 T ⁢ K 𝒩𝒩 ⁢ α 𝒩 - λα 𝒩 T ⁡ ( diag ⁡ ( K 𝒩𝒩 ) + 2 ⁢ λ ⁢ ⁢ K 𝒩𝒪 ⁢ α 𝒪 - 2 ⁢ K 𝒩𝒪 ⁢ α 𝒪 ) ) , wherein O is a set containing learned support vectors, N is a set containing the new batch data, α O represents a weight of support vectors from the first support vector machine, K NN represents a kernel matrix of the new batch data, K NO represents a kernel matrix between the new batch data and support vectors from the first support vector machine, α N represents desired weights of support vectors from the new support vector machine, and λ is a parameter to adjust weights from the first support vector machine and from the new support vector machine jointly.