Local search quantization (LSQ)

encoding_icm(X, oldB, C, ilsiter, icmiter, randord, npert, cpp=true, V=false) -> B

Given data and chain codebooks, find codes using iterated local search with ICM.

Arguments

• X::Matrix{T}: d-by-n data to quantize
• OldB::Matrix{Int16}: m-by-n initial set of codes
• ilsiter::Integer: Number of iterated local search (ILS) iterations
• icmiter::Integer: Number of iterated conditional modes (ICM) iterations
• randord::Bool: Whether to use random order
• npert::Integer: Number of codes to perturb
• cpp::Bool=true: Whether to use the c++ implementation
• V::Bool=false: Whehter to print progress

Returns

• B::Matrix{Int16}: m-by-n matrix with the new codes

train_lsq(X, m, h, R, B, C, niter, ilsiter, icmiter, randord, npert, cpp=true, V=false) -> C, B, obj

Train a local-search quantizer. This method is typically initialized by Chain quantization (ChainQ)

Arguments

• X::Matrix{T}: d-by-n data to quantize
• m::Integer: Number of codebooks
• h::Integer: Number of entries in each codebook (typically 256)
• R::Matrix{T}: d-by-d rotation matrix for initialization
• B::Matrix{Int16}: m-by-n matrix with pre-trained codes for initialization
• C::Vector{Matrix{T}}: m-long vector with d-by-h matrices. Each matrix is a pretrained codebook of size approximately d-by-h
• niter::Integer: Number of iterations to use
• ilster::Integer: Number of iterated local search (ILS) iterations
• icmiter::Integer: Number of iterated conditional modes (ICM) iterations
• randord::Bool: Whether to visit the nodes in a random order in ICM
• npert::Integer: Number of codes to perturb
• cpp::Bool: Whether to use a c++ implementation for encoding
• V::Bool: Whether to print progress

Returns

• C::Vector{Matrix{T}}: m-long vector with d-by-h matrix entries. Each matrix is a codebook of size approximately d-by-h
• B::Matrix{Int16}: m-by-n matrix with the codes
• obj::Vector{T}: niter-long vector with the quantization error after each iteration