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Kuyera Mitemo yeNeural Networks
Basics
Basics GUIDE
Iyo Neural Tangent Kernel (NTK) chishandiso chemasvomhu chinoratidza kuti neural network yakafara kwazvo inoita seyakatarwa, yakagadziriswa kernel nzira panguva yekudzidziswa.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
It matters because it turns mysterious deep learning into something with closed-form, analyzable equations.
Yakaunzwa naJacot, Gabriel, naHongler muna 2018, NTK dzidziso inodzidza zvinoitika sematanho etiweki anova akafara zvisingaite. Mumuganho iwoyo, kudzidziswa ne gradient descent kunomira kuve rwendo rwemusango rusina mutsara: maparamendi etiweki haafambi kubva payakagadzika kutanga (iyo 'usimbe kudzidzira' hutongi), uye basa rainokokorodza rinoshanduka rakaita mutsara, richitongwa nekernel inoramba iripo panguva yese yekudzidziswa. Iyo kernel - yemukati chigadzirwa chegradient nekuremekedza ma paramita - ndiyo NTK. Nekuti kernel regression ine mhinduro chaidzo, unogona kufanotaura kuburitswa kwenetiweki yakadzidziswa pasina kuidzidzisa. NTK yakatsanangura kuti nei yakakura overparametered network ichigona kukwana data asi ichiri kuita zvakajairika, uye inobatanidza kudzidza kwakadzama kumakumi emakumi emakore ezvinonzwisisika kernel nzira uye Gaussian maitiro.
Kufanotaura netiweki yakakura yekudzidzira dynamics nekuongorora kusarudza mareti ekudzidza pasina anodhura bvunzo inomhanya
Kushandisa NTK-based metrics kukwirisa mumiriri zvivakwa zvakachipa panguva yekutsvaga neural architecture
Kutsanangura ne theoretically kuti nei overparametered network ichichinja kusvika zero kudzidziswa kurasikirwa uye ichiri kuita generalize
Kugadzira kernel approximations (NTK-yakafuridzirwa Gaussian maitiro) emabasa ane diki dhata uko chaiko kusavimbika fungidziro ine basa.
NTK ndiyo musana wedzidziso yemazuva ano yakadzama-yekudzidza, asi chaiyo inogumira network inodzidzira maficha - chimwe chinhu chinorasikirwa nemufananidzo wekernel. Tsvagiridzo ikozvino inotarisa pamukaha uripo pakati pe'usimbe' NTK maitiro uye 'kupfuma' maitiro-yekudzidza hurumende, uye pakushandisa NTK kufanotaura mashandiro ezvivakwa, kutungamira neural architecture yekutsvaga, uye yakasungwa generalization. Tarisira dzidziso dzakasanganiswa dzinobata kana network ichiita senge kernels maringe kana vachidzidza zvinomiririra.
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Iyo Neural Tangent Kernel (NTK) chishandiso chemasvomhu chinoratidza kuti neural network yakafara kwazvo inoita seyakatarwa, yakagadziriswa kernel nzira panguva yekudzidziswa. Izvo zvine basa nekuti inoshandura isinganzwisisike yakadzika kudzidza kuita chimwe chinhu chine yakavharwa-fomu, inoongororwa equations.
Mhedzisiro yepakati NTK mhedzisiro ndeyekuti mune isingaperi-hupamhi muganho kernel inochinjika kune yakagadziriswa kukosha uye inoramba yakagadzikana mukati me gradient-kudzika kudzidziswa.
Iyo NTK ndeye K(x,x') = ⟨∇θ f(x), ∇θ f(x')⟩, chigadzirwa chemukati chemagetsi ezvinobuda maererano nemaparamita.
Iyo NTK yakaunzwa mubepa re2018 naArthur Jacot, Franck Gabriel, naClément Hongler.
Mukudzidzira usimbe, maparamendi e-network anogara padyo nemaitiro avo ekutanga uye zvinobuda zvinoshanduka zvine mutsetse, izvo zvinoita kuti iyo yakagadziriswa-kernel ongororo ishande.
Kernel regression ine yakavharwa-fomu mhinduro, saka mumuganho weNTK munhu anogona kufembera nekuongorora zvakabuda netiweki yakadzidziswa.
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InoteveraGaidhi rinotevera
Kuyera Mitemo yeNeural Networks
Basics