quiz bu lëkkale ak tegtal · Diggante Niveau

Laaj ak tontu bu gaaw ci degrade bu Nesterov

Saytu courant ak gradient yiy xool kanam, jubbanti momentum, yaatuwaayu tolluwaayu convex, njëg buñ mëna méngale, Nadam, ak jéego buy xool kanam ci nimero.

Yooni njiit yu jëm ciDegree bu gaaw bu Nesterov
Laaj 1 de 8

Lan mooy xalaat bi gëna fësal degrade bu gaaw bu Nesterov buñu ko méngale ak momentum bu yàgg bi?

Xoolaatal laaj bu nekk8 laaj

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

  1. Lan mooy xalaat bi gëna fësal degrade bu gaaw bu Nesterov buñu ko méngale ak momentum bu yàgg bi?
    • Dafay dindi momentum bi lëmm
    • Dafay jëfandikoo tolluwaayu jàng bu takku bu 1.0
    • Dafay jàngat degrade bi ci barab bu ñuy xoole kanam, du ci barab bi ñu nekk leegi
    • Dafay dox ludul te amul ay mini-lot
  2. Ban tolluwaayu konwergensi la anam wi Nesterov mëna am ci jafe-jafe konvex yu nooy yi?
    • Komànd 1/k^2
    • Komànd 1/k
    • Komànd 1/log k
    • Amul njëg buñu mëna garanti
  3. Kan moo njëkka dugal xeetu gradient bu gaaw bii?
    • Geoffrey Hinton ci 2012
    • Isaac Newton
    • Yowaana von Neumann
    • 1983
  4. Lan moo waral gradient biy xool kanam di jàppale ci wetu minima yu xawa sëgg yi?
    • Dafay yokk ni ñuy jàngee
    • Dafay waajal lu ëpp ba noppi def njuumte balaa muy am
    • Dafay efaase kàddu gaawaay
    • Dafay tànn yoon wi jéego yi di jaar
  5. Ci jëf, naka la njëgu xayma bu momentum Nesterov di méngoo ak momentum classique bi?
    • Lu tollu ci noonu la, gërëm ci yeesal buñ defaraat ci algebra
    • Lu tollu ci fukki yoon lu ëpp
    • Dafay laaj ñaareelu derivatif ci jéego bu nekk
    • Mënu ko xayma ci GPU yi
  6. Ban optimisatër moo boole Nesterov xool ci kanam ak scaling bu nuroo ak Adam?
    • RMSprop
    • Adagrad
    • Nadam
    • LBFGS
  7. Using the stated look-ahead form, theta = 10, learning rate = 0.1, beta = 0.9 and velocity = 2 give which evaluation point?
    • 10.18
    • 9.82
    • 8.20
    • 10.90
  8. If beta is zero in the guide’s Nesterov look-ahead formula, where is the gradient evaluated?
    • At a point displaced by the full old velocity
    • At the previous validation score
    • At an arbitrary future minibatch
    • At the current parameter position