從粗到細 實踐中，一般先進行初步范圍搜索，然后根據(jù)好結(jié)果出現(xiàn)的地方，再縮小范圍進行更精細的搜索。 先參考相關(guān)論文，以論文中給出的參數(shù)作為初始參數(shù)。 如果找不到參考，那么只能自...
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IP屬地：貴州
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深度學(xué)習(xí)調(diào)參技巧
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Knowledge transfer summary-2
所謂“知識精煉”我的理解就是將一個訓(xùn)練好的復(fù)雜模型的“知識”遷移到一個結(jié)構(gòu)更為簡單的網(wǎng)絡(luò)中，或者通過簡單的網(wǎng)絡(luò)去學(xué)習(xí)復(fù)雜模型中“知識”或模仿復(fù)雜模型的行為。當(dāng)然“知識”的定義...
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網(wǎng)絡(luò)量化小結(jié)
網(wǎng)絡(luò)量化作為一種重要的模型壓縮方法，大致可以分為兩類： 直接降低參數(shù)精度典型的工作包括二值網(wǎng)絡(luò)，三值網(wǎng)絡(luò)以及XNOR-Net. HORQ和Network Sketching相...
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Speeding-up CNN using CP-Decomposition
Approach We propose a simple two-step approach for speeding up convolution layers withi...
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Exploiting Linear Structure Within CNNApproach Matrix Decomposition Higher Order Tensor Approximations Monochromatic Convolut...
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Dynamic Network SurgeryApproach Han song recently propose to compress DNN by deleting unimportant parameters a...
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Speed up CNN with Low Rank ExpansionsApproach Experiment References:Speeding up Convolutional Neural Networks with Low Rank ...
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Learning Structured Sparsity in DNNApproach The optimization target of learning the filter-wise and channel-wise structure...
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Fixed-point Factorized NetworksApproach Fixed-point Factorization Full-precision Weights Recovery The quantized weight...
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Quantized CNN for Mobile DevicesApproach Firstly, we introduce an efficient test-phase computation process with the net...
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Network SketchingApproach Approximating the Filters Speeding-up the Sketch Model Experiment References:N...
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Incremental network quantizationApproach We present INQ which incorporates three interdependent operations: weight part...
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Soft weight-sharing for DNNApproach where p(w) is the prior over w and p(D|w) is the model likelihood. After re-tr...
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Deep CompressionApproach We introduce “deep compression”, a three stage pipeline: pruning, trained quan...
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Network pruning summary
一直以來，網(wǎng)絡(luò)剪枝都是模型壓縮中的重要方法。按照被剪對象的粒度來分，大致可以分為三類： 針對權(quán)重剪枝，最具代表性的工作是韓松發(fā)表在NIP'15上的文章 “Learning b...
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Dynamic Network Surgery
Approach Han song recently propose to compress DNN by deleting unimportant parameters a...
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Pruning CNN for resource efficient inferenceApproach The proposed scheme for pruning consists of the following steps: Fine-tune the...