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Abstract: Neural image compression, necessary in various machine-to-machine communication scenarios, suffers from its heavy encode-decode structures and inflexibility in switching between different ...

Abstract: In recent years, deep learning has shown significant progress for image compression compared to traditional image compression methods. Although conventional standard-based methods are still ...

Random rotation: Multiply the input vector by a fixed random orthogonal matrix. This makes each coordinate follow a known Beta(d/2, d/2) distribution. Lloyd-Max scalar quantization: Quantize each ...

Topics python deep-learning numpy transformer attention quantization vector-quantization model-compression inference-optimization memory-optimization kv-cache post-training-quantization llm ...