Generalized entropy and quantization problems
WebJul 1, 1992 · New results concerning the entropy lower bound are derived. Continuity of the entropy and attaining the minimum entropy are proved in the case where the mixture is … WebApr 11, 2024 · This entropy amounts to Shannon’s entropy associated with a Wigner distribution. Recall the Wigner distribution of some f \in L^2 ( {\mathbb {R}}^d) is given by: \begin {aligned} Wf (x,p)= \frac {1} { (2 \pi \hbar )^d} \int \limits _ { {\mathbb {R}}^d} f (x+y/2) \overline {f (x-y/2)} e^ {- \frac {i} {\hbar }y \cdot p} \textrm {d}y~. \end {aligned}
Generalized entropy and quantization problems
Did you know?
WebFeb 18, 2024 · Entropy and differential entropy are important quantities in information theory. A tractable extension to singular random variables-which are neither discrete nor continuous-has not been...
WebNov 29, 2024 · To train the quantized network with learnable input thresholds, we introduce a generalized straight-through estimator (G-STE) for intractable backward derivative calculation w.r.t. threshold parameters. Additionally, we consider entropy preserving regularization to further reduce information loss in weight quantization. WebZador's classic result for the asymptotic high-rate behavior of entropy-constrained vector quantization is recast in a Lagrangian form which better matches the Lloyd algorithm used to optimize...
WebThe LBG algorithm is a generalization of the scalar quantization design algorithm introduced by Lloyd, and hence is also often called the generalized Lloyd algorithm or GLA. Interestingly, this algorithm was known earlier in the pattern recognition community as the k -means algorithm. Webover all mapping rules achieving a particular entropy without fixing M. One algorithm that finds a local minimum of distortion of the M−level quantizer has been proposed by Linde, Buzo and Gray[2] and is called generalized Lloyd algorithm(GLA). The design of GLA-quantizers is rather time-consuming. With the purpose of alleviating this ...
WebQuantization, in mathematics and digital signal processing, is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often with a finite number of elements. Rounding and truncation are typical examples of quantization processes.
Webthis style of quantization achieves higher efficiency than conventional schemes. 4. Quantization based on Weighted Entropy 4.1. Weight Quantization The high-level idea of our weight quantization approach is to group weights into N clusters in a way to have more clusters for important ranges of weights, assign a represen- credit right nowWeba generalized entropy, introduced earlier by the rst author is optimized under various conditions and it is shown that Maxwell{Boltzmann distribution, Raleigh distribution and … credit right debit leftWebDec 1, 2014 · Motivated by recent results providing an operational meaning to Rényi entropy [1], we study the maximization of the Rényi entropy rate (or "Rényi rate") over the class of stochastic processes... credit rightsexperts.comWebMar 21, 2024 · The problem is then solved by selecting top-k differentials, in which the corresponding modules are jointly optimized and quantized. Extensive experiments demonstrate that our method successfully reduces the performance drop and is generalized to different neural networks and PTQ methods. credit risk analysis meaningWebJul 7, 2013 · While there are ways to demonstrate that physical observables in Schrödinger and polymer quantizations converge to the same value in the appropriate limit [56,57], analysis of the quantum entropy... buckle summer clithesWebApr 8, 2024 · Recently, unification of general relativity and quantum mechanics is a difficult problems of the theoretical physics due to singularity of a black hole where a certain scalar curvature diverges. credit right offWebQuantization is considered as one of the most effective methods to optimize the inference cost of neural network models for their deployment to mobile and … credit rights act