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Monotonicity • monotonicity 10 Let K =(A, ⊕, ⊗, 0, 1) be a semiring, and ≤ a partial ordering over A. We say K is monotonic if for all a, b, c ∈ A (a ≤ b) ⇒ (a ⊗ c ≤ b ⊗ c) (a ≤ b) ⇒ (c ⊗ a ≤ c ⊗ b) Liang Huang Dynamic Programming
• monotonicity Monotonicity Let K =(A, ⊕, ⊗, 0, 1) be a semiring, and ≤ a partial ordering over A. We say K is monotonic if for all a, b, c ∈ A (a ≤ b) ⇒ (a ⊗ c ≤ b ⊗ c) (a ≤ b) ⇒ (c ⊗ a ≤ c ⊗ b) • optimal substructure in dynamic programming Liang Huang 10 Dynamic Programming
Page 1 and 2: Dynamic Programming Algorithms in S
Page 3 and 4: Dynamic Programming Liang Huang 3 D
Page 5 and 6: Dynamic Programming • Dynamic Pro
Page 7 and 8: Two Dimensional Survey traversing o
Page 9 and 10: Motivations for Semirings • in a
Page 11 and 12: Definitions A monoid is a triple (A
Page 13 and 14: Definitions A monoid is a triple (A
Page 15 and 16: Examples Semiring Set ⊕ ⊗ 0 1 i
Page 17 and 18: Ordering • idempotent 9 A semirin
Page 19 and 20: Ordering • idempotent A semiring
Page 21: Monotonicity • monotonicity 10 Li
Page 25 and 26: • monotonicity Monotonicity Let K
Page 27 and 28: • monotonicity Monotonicity Let K
Page 31 and 32: Viterbi Algorithm for DAGs 1. topol
Page 33 and 34: Examples Liang Huang 15 Dynamic Pro
Page 35 and 36: Examples • [Number of Paths in a
Page 41 and 42: Example: Word Alignment Liang Huang
Page 43 and 44: Dijkstra Algorithm • Dijkstra doe
Page 51 and 52: Dijkstra Algorithm • keep a cut (
Page 53 and 54: Viterbi vs. Dijkstra • structural
Page 61 and 62: What if both work? monotonic optimi
Page 65 and 66: Background: CFG and Parsing Liang H
Page 67 and 68: Hypergraphs and Deduction tails : a
Page 69 and 70: Hypergraphs and Deduction tails : a
Page 71 and 72: Weight Functions and Semirings d(u)
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Weight Functions and Semirings d(u)
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Viterbi Algorithm for DAGs 1. topol
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Example: CKY Parsing • parsing wi
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Forward Variant for DAHs 1. topolog
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Example: Treebank Parsers • State
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Dijkstra Algorithm • keep a cut (
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Knuth (1977) Algorithm • keep a c
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Knuth (1977) Algorithm • keep a c
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Example: A* Parsing • Use A* sear
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Same Picture Again monotonic optimi
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Conclusion • surveyed two general
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