Name
Abstract | ||
|---|---|---|
Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary issue of designing classification algorithms that can deal with more complex outputs, such as trees, sequences, or sets. More generally, we consider problems involving multiple dependent output variables, structured output spaces, and classification problems with class attributes. In order to accomplish this, we propose to appropriately generalize the well-known notion of a separation margin and derive a corresponding maximum-margin formulation. While this leads to a quadratic program with a potentially prohibitive, i.e. exponential, number of constraints, we present a cutting plane algorithm that solves the optimization problem in polynomial time for a large class of problems. The proposed method has important applications in areas such as computational biology, natural language processing, information retrieval/extraction, and optical character recognition. Experiments from various domains involving different types of output spaces emphasize the breadth and generality of our approach. |
Year | Venue | Keywords |
|---|---|---|
2005 | Journal of Machine Learning Research | computational intelligence,class attribute,interdependent output variables,complex output,large margin methods,structured output space,classification algorithm,output space,classification problem,arbitrary input,computational biology,multiple dependent output variable,polynomial time,information retrieval,machine learning,natural language processing,generating function,optimization problem,optical character recognition,quadratic program |
Field | DocType | Volume |
Computer science,Structured prediction,Theoretical computer science,Input/output,Artificial intelligence,Quadratic programming,Time complexity,Optimization problem,Mathematical optimization,Computational intelligence,Optical character recognition,Statistical classification,Machine learning | Journal | 6, |
ISSN | Citations | PageRank |
1532-4435 | 1043 | 46.53 |
References | Authors | |
21 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ioannis Tsochantaridis | 1 | 2861 | 155.43 |
| Thorsten Joachims | 2 | 17387 | 1254.06 |
| Thomas Hofmann | 3 | 10064 | 1001.83 |
| yasemin altun | 4 | 2463 | 150.46 |