Online Learned Continual Compression with Adaptive Quantization Modules

ICML 2020 Lucas CacciaEugene BelilovskyMassimo CacciaJoelle Pineau

We introduce and study the problem of Online Continual Compression, where one attempts to simultaneously learn to compress and store a representative dataset from a non i.i.d data stream, while only observing each sample once. A naive application of auto-encoders in this setting encounters a major challenge: representations derived from earlier encoder states must be usable by later decoder states... (read more)

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