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Glossario IA

Il dizionario completo dell'Intelligenza Artificiale

162
categorie
2.032
sottocategorie
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termini
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Per-Batch Calibration

Process of adjusting scale and zero-point quantization parameters for each data batch, optimizing representation accuracy in real-time.

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Dynamic Scale

Variable quantization parameter that adapts the conversion factor between floating-point and integer numbers according to the statistical distribution of the current batch.

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Dynamic Zero-Point

Offset value dynamically adjusted to ensure that zero in floating-point is represented exactly after quantization, varying per batch.

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Dynamic Min-Max

Calibration algorithm that determines quantization bounds by calculating min and max values of each activation batch by batch.

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Dynamic Entropy

Calibration method based on minimizing KL divergence entropy, dynamically recalculated to optimize the quantized distribution.

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Dynamic KL-Divergence

Calibration technique measuring divergence between original and quantized distributions, dynamically adjusted to minimize information loss.

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Dynamic Post-Training Quantization

Quantization approach applied after model training, using runtime statistics to determine optimal quantization parameters.

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Adaptive Calibration

Mechanism for continuous adjustment of quantization parameters based on the evolving characteristics of input data in production.

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Dynamic Quantization Factor

Variable multiplicative coefficient applied during activation conversion, dynamically optimized based on the amplitude of batch values.

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Dynamic Precision

Ability of a quantization system to maintain optimal precision by continuously adapting parameters to variations in data distribution.

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Dynamic Error Reconstruction

Technique evaluating and minimizing quantization error in real-time, adjusting parameters to optimize reconstruction fidelity.

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Dynamic Bit Optimization

Strategy adapting the number of quantization bits per layer or per batch based on sensitivity and activation characteristics.

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Dynamic Hybrid Quantization

Combination of static and dynamic approaches where certain weights are quantized statically while activations use batch-by-batch dynamic calibration.

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Active-Passive Calibration

Hybrid method alternating between active calibration (frequent recalculation) and passive (caching) to optimize performance and accuracy.

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Dynamic Thresholding

Technique adapting quantization saturation and truncation thresholds according to the evolving statistical characteristics of activations.

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