Meta-Mibvunzo Yekudzidza

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

1. Chii chinonzi meta-kudzidza, kana kuti 'kudzidza kudzidza,' kunonyanyovavarira kuwana?
   • Kukurumidza kugadzirisa kumabasa matsva kubva kumuenzaniso mishoma
   • Kurangarira imwe hofori dataset
   • Kubvisa kudiwa kwekudzidziswa chero kupi zvako
   • Kumanikidza modhi kusvika zero size
2. Panguva yekudzidziswa kwemeta, iyo data inowanzogadziriswa sei?
   • Sebasa rimwechete risina kupatsanurwa
   • Sezvo akawanda mabasa, rimwe nerimwe rine seti yekutsigira uye seti yemubvunzo
   • Semufananidzo mumwe wakadzokororwa
   • Seruzha rusina kunyorwa chete
3. MAML inodzidzei?
   • A fixed classifier isingachinji
   • A dataset of negatives
   • A modhi yekutanga iyo inogona kukwenenzverwa kumabasa matsva mumatanho mashoma
   • A compression codec
4. Ko Prototypical Networks inoronga sei mienzaniso mitsva?
   • Nekugadzira mifananidzo mitsva
   • Nekuyeuka kukosha kwepixel
   • Nekungofungidzira
   • Nekuvaenzanisa neakadzidza kirasi prototypes mune embedding nzvimbo
5. Ndeipi basa reMAML yemukati loop?
   • Kugadzirisa modhi kune rimwe basa rine nhanho shoma dzegradient
   • Kubatanidza dataset
   • Kudzima parameters
   • Kuisa mwero wekudzidza kusvika zero
6. How does GPT-3 perform the few-shot demonstrations in the cited paper?
   • By updating all model weights after every example
   • By including examples in the prompt without gradient updates or fine-tuning
   • By storing one prototype per class
   • By running a MAML inner loop during inference
7. In Reptile, how is the meta-initialization updated after adapting on a sampled task?
   • Replace the model with a nearest-neighbor table
   • Average class labels without updating parameters
   • Move the initialization toward the task-adapted parameters
   • Train a separate model for every example
8. What computational shortcut distinguishes Reptile from the second-order MAML formulation?
   • It requires no gradient steps
   • It stores only class prototypes
   • It trains without tasks or task-specific data
   • It can use a first-order update without computing second-order derivatives