Unstructured data is messy, scattered, and multimodal — making it hard to manage and essential to control for successful ...

Consider the problem where a statistician in a two-node system receives rate-limited information from a transmitter about marginal observations of a memoryless process generated from two possible ...

There are two kinds of compression. Lossy compression can make audio files truly tiny — up to a tenth of their original size. But to do that, it discards some of the original information.

A track that has been lossy compressed, however, no longer has all of the original data, and there’s no way to get it back when you decompress it. There are varying degrees of lossy compression.

TensorFlow Compression (TFC) contains data compression tools for TensorFlow. You can use this library to build your own ML models with end-to-end optimized data compression built in. It's useful to ...

Quantization is a technique for lossy compression.” Accuracy A decision about data format is basically a decision about accuracy. “Is 8-bit data for activations good enough, or do I need to use 10-bit ...

Lossless and lossy compression of water-column profile data from multibeam echosounders based on image predictions and multiple-context entropy-encoding Authorship SCIMAGO INSTITUTIONS RANKINGS ...

Lossless compression means nothing is lost or left out when data is squeezed into smaller packages. This differs from lossy compression, which is what the image compression format JPEG uses.

Adaptive compression algorithms dynamically adjust their compression methods based on the data being compressed. They can switch between lossless and lossy techniques to optimize compression based on ...

Our method comprises noise injection followed by lossy compression. We show that, when appropriately matching the lossy compression to the distribution of the added noise, the compressed examples ...