MSR India Interview Questions and Answers

MoE models, or Mixture of Experts models, combine multiple models to improve accuracy and performance.

• MoE models consist of multiple sub-models, or experts, that specialize in different areas of the input space.

• Each expert is responsible for a specific region of the input space, improving accuracy by focusing on relevant data.

• The gating network determines which expert to use for a given input, allowing for dynamic mode...read more

Sparse matrix multiplication involves multiplying two matrices represented as lists of (index, value) pairs for rows and columns.

• Use the (index, value) pairs to calculate the product of the matrices efficiently.

• Only multiply the non-zero elements of the matrices to save computation time.

• Combine the results to get the final product matrix.

Gradient computation is faster without dropout due to reduced complexity

• Gradient computation is faster without dropout because dropout introduces randomness which slows down the process

• Dropout increases the complexity of the network by randomly dropping units during training, leading to longer computation times

• Without dropout, the network is more deterministic and the gradient computation can be done more efficiently

• Ex...read more