Generative and Discriminative Latent Variable Grammars

author: Slav Petrov, Google Research New York
published: March 26, 2010, recorded: December 2009, views: 120

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Slides

Slides
0:00	Generative and Discriminative Latent Variable Grammars
0:13	Generative and Discriminative Latent Variable Grammars
0:53	Lexicalized Grammars (1)
0:58	Lexicalized Grammars, Disadvantages (1)
1:02	Lexicalized Grammars , Disadvantages (2)
1:23	Latent Variable Grammars (1)
1:48	Latent Variable Grammars, Advantages (1)
1:58	Latent Variable Grammars, Advantages (2)
2:00	Latent Variable Grammars (2)
2:01	Latent Variable Grammars (3)
2:15	Latent Variable Grammars (4)
2:23	Latent Variable Grammars (5)
2:33	Latent Variable Grammars (6)
2:48	Latent Variable Grammars (7)
2:50	Latent Variable Grammars (8)
2:52	Latent Variable Grammars (9)
3:06	Latent Variable Grammars (10)
3:16	Generative vs. Discriminative
3:18	Generative (1)
3:21	Generative (2)
3:25	Generative (3)
3:31	Generative (4)
3:38	Discriminative (1)
3:48	Discriminative (2)
3:52	Discriminative (3)
3:58	Discriminative (4)
4:23	Generative Training (1)
4:23	Generative Training (2)
4:25	Generative Training (3)
4:30	Generative Training (4)
4:32	Generative Training (5)
4:39	Generative Training (6)
4:53	Generative Training (7)
4:54	Generative Training (8)
4:55	Generative Training (9)
4:57	Generative Training (10)
5:23	Generative Training - use EM
5:33	Incremental Learning (Pronouns) (1)
5:43	Incremental Learning (Pronouns) (2)
6:03	Incremental Learning (Determiners) (1)
6:08	Incremental Learning (Determiners) (2)
6:12	Incremental Learning (Determiners) (3)
6:27	Adaptive Splitting (1)
6:45	Adaptive Splitting (2)
6:52	Adaptive Splitting (3)
6:57	Adaptive Splitting (4)
7:05	Adaptive Splitting (5)
7:25	Adaptive Splitting (6)
7:53	Number of Phrasal Subcategories (1)
8:03	Number of Phrasal Subcategories (2)
8:13	Number of Phrasal Subcategories (3)
8:15	Number of Lexical Subcategories (1)
8:18	Number of Lexical Subcategories (2)
8:28	Generative Performance (1)
8:53	Generative Performance (2)
9:03	Generative Performance (4)
9:03	Generative Performance (3)
9:04	Generative Performance (5)
9:06	Generative Performance (6)
9:13	Generative Performance - Model
9:31	Objective Functions (1)
9:33	Objective Functions (2)
9:43	Discriminative Objective Function (1)
9:49	Discriminative Objective Function (2)
10:15	Discriminative Objective Function (3)
10:18	Discriminative Training (1)
10:20	Discriminative Training (2)
11:18	Discriminative Training (3)
11:23	Hierarchical Features (1)
11:33	Hierarchical Features (2)
11:43	Hierarchical Features (3)
11:46	Hierarchical Features (4)
11:52	Hierarchical Features (5)
11:53	Hierarchical Features (6)
12:06	Hierarchical Features (7)
12:20	Hierarchical Features (8)
12:22	Hierarchical Features (9)
12:25	Hierarchical Features (10)
12:26	Hierarchical Features (11)
12:27	Hierarchical Features (12)
12:31	Parameter Battle (1)
12:53	Parameter Battle (2)
13:09	Parameter Battle (3)
13:24	Parameter Explosion (1)
13:31	Parameter Explosion (2)
13:39	Parameter Explosion (3)
13:40	Parameter Explosion (4)
13:42	Parameter Explosion (5)
13:45	Hierarchical Features (1)
13:46	Hierarchical Features (2)
13:49	Hierarchical Features (3)
13:50	Hierarchical Features (4)
13:51	Hierarchical Features (5)
14:06	Hierarchical Features (6)
14:09	Hierarchical Features (7)
14:13	Hierarchical Features (8)
14:17	Hierarchical Features (9)
14:18	Hierarchical Features (10)
14:20	Hierarchical Features (11)
14:22	Hierarchical Features (12)
14:39	Hierarchical Features (13)
14:41	Multi-Scale Latent Variable Grammars (1)
15:22	Multi-Scale Latent Variable Grammars (2)
15:23	Multi-Scale Latent Variable Grammars (3)
15:25	Multi-Scale Latent Variable Grammars (4)
15:31	Compact, Discriminative Grammars
16:26	Generative vs. Discriminative (1)
16:27	Generative vs. Discriminative (2)
17:03	Generative vs. Discriminative (3)
17:07	Generative vs. Discriminative (4)
17:23	Final Results (English-Brown) (1)
17:24	Final Results (English-Brown) (2)
17:25	Multi-Lingual Results
17:28	Complexity Comparison
17:31	Error Analysis (1)
17:32	Error Analysis (2)
17:34	Error Analysis (3)
17:54	Conclusions and Future Work (1)
17:55	Conclusions and Future Work (2)
17:56	Conclusions and Future Work (3)
18:03	Thank you!

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Description

Latent variable grammars take an observed (coarse) treebank and induce more fine-grained grammar categories, that are better suited for modeling the syntax of natural languages. Estimation can be done in a generative or a discriminative framework, and results in the best published parsing accuracies over a wide range of syntactically divergent languages and domains. In this paper we highlight the commonalities and the differences between the two learning paradigms and speculate that a hybrid approach might outperform either respectively.