QATS is a new polylog-time approximate decoding procedure for HMMs that builds admissible state sequences by locally maximizing likelihoods over paths with at most three segments via adaptive ternary segmentation and cumulative sum storage.
RcppArmadillo: Accelerating R with high-performance C++ linear algebra
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iglm is an R package that implements scalable regression for outcomes under interference in connected populations using pseudo-likelihood optimization with theoretical guarantees.
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Quick Adaptive Ternary Segmentation: An Efficient Decoding Procedure For Hidden Markov Models
QATS is a new polylog-time approximate decoding procedure for HMMs that builds admissible state sequences by locally maximizing likelihoods over paths with at most three segments via adaptive ternary segmentation and cumulative sum storage.
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R Package iglm: Regression under Interference in Connected Populations
iglm is an R package that implements scalable regression for outcomes under interference in connected populations using pseudo-likelihood optimization with theoretical guarantees.