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Reducing Catastrophic Forgetting in Neural Networks via Gaussian Mixture Approximation
Our paper studies the continual learning (CL) problems in which data comes in sequence and the trained models are expected to be capable of utilizing existing knowledge to solve new tasks without losing performance on previous ones.
Bag of biterms modeling for short texts
Furthermore, many applications often face with massive and dynamic short texts, causing various computational challenges to the current batch learning algorithms.
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