Advanced Structured Prediction

Advanced Structured Prediction

Structured Prediction Theory and Voted Risk Minimization

We present a general theoretical analysis of structured prediction with a series of new results. We give new data-dependent margin guarantees for structured prediction for a very wide family of loss functions and a general family of hypotheses, with an arbitrary factor graph decomposition. These are the tightest margin bounds known for both standard multi-class and general structured prediction...

Structured Prediction Theory Based on Factor Graph Complexity

We present a general theoretical analysis of structured prediction with a series of new results. We give new data-dependent margin guarantees for structured prediction for a very wide family of loss functions and a general family of hypotheses, with an arbitrary factor graph decomposition. These are the tightest margin bounds known for both standard multi-class and general structured prediction...

Boosting Ensembles of Structured Prediction Rules

We present a boosting algorithm for structured prediction with theoretical guarantees for learning accurate ensembles of several structured prediction rules for which no prior knowledge is assumed.

HC-Search: A Learning Framework for Search-based Structured Prediction

Structured prediction is the problem of learning a function that maps structured inputs to structured outputs. Prototypical examples of structured prediction include part-ofspeech tagging and semantic segmentation of images. Inspired by the recent successes of search-based structured prediction, we introduce a new framework for structured prediction called HC-Search. Given a structured input, t...