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Everything about Forward–backward algorithm
Inference algorithm for hidden Markov models
The forward–backward algorithm is an inference algorithm for hidden Markov models which computes the posterior marginals of all hidden state variables given a sequence of observations/emissions, i.e. it computes, for all hidden state variables, the distribution. This inference task is usually called smoothing. The algorithm makes use of the principle of dynamic programming to efficiently compute the values that are required to obtain the posterior marginal distributions in two passes. The first pass goes forward in time while the second goes backward in time; hence the name forward–backward algorithm. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Forward–backward algorithmA 5-minute orientation
- Skim a recent paper: Strongly convergent inertial forward-backward-forward algorithm without on-line rule for variational inequalitiesInfluential work since 2022
- Pick up a classic book: Artificial intelligenceThe most-reprinted book on the subject
- Read the landmark paper: An Inertial Forward-Backward Algorithm for Monotone InclusionsCited 386 times
- Go sideways: DyadicsA closely related topic
- Go sideways: Kernel embedding of distributionsA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
An Inertial Forward-Backward Algorithm for Monotone Inclusions
Adaptive Forward-Backward Greedy Algorithm for Learning Sparse Representations
Baum's forward-backward algorithm revisited
A block coordinate variable metric forward–backward algorithm
A forward–backward stochastic algorithm for quasi-linear PDEs
Forward-Backward-Half Forward Algorithm for Solving Monotone Inclusions
Convergence rate of inertial Forward–Backward algorithm beyond Nesterov’s rule
On the memory complexity of the forward–backward algorithm
🆕 Influential since 2022
Strongly convergent inertial forward-backward-forward algorithm without on-line rule for variational inequalities
A Backward–Forward Sweep Algorithm for Distribution System State Estimation
A Primal-Dual Forward-Backward Splitting Algorithm for Distributed Convex Optimization
A Multitasking-Based Constrained Multi-Objective Evolutionary Algorithm With Forward and Backward Stages
A new modified forward–backward–forward algorithm for solving inclusion problems
đź“š Books worth reading
Artificial intelligenceStuart J. Russell, Peter Norvig · 1994
Game TheoryMichael Maschler, Eilon Solan · 2013
Why programs failAndreas Zeller · 2005
Data structures using C++D. S. Malik · 2010
Subset selection in regressionMiller, Alan J. · 1990
Coding the MatrixPhilip N. Klein · 2013
Fault tolerant computer architectureDaniel J. Sorin · 2009
Tools and Algorithms for the Construction and Analysis of SystemsNir Piterman · 2013
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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