Name
Title | ||
|---|---|---|
Active Learning Without Unlabeled Samples: Generating Questions And Labels Using Monte Carlo Tree Search |
Abstract | ||
|---|---|---|
Classification of short texts (e.g. reviews, sentences) is a well-defined task, usually attempted in regimes where data is abundant. This is, however, not always the case. Limited data availability is very common in industrial settings and seriously hinders the performance of any classification task - it is not always obvious how to perform data augmentation. In this work, we apply the Recurrent Neural Network and Monte Carlo Tree Search (MCTS) to generate unlabelled questions. We use Human In-the-Loop to help decide whether 1) the generated questions are meaningful or not 2) label them into correct categories. We show that generated data leads to improved classification performance in comparison to the vanilla dataset. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/BigData47090.2019.9006276 | 2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) |
Keywords | Field | DocType |
Sentence generation, MCTS, active learning, Human-In-the-Loop | Data mining,Monte Carlo tree search,Active learning,Data availability,Computer science,Recurrent neural network,Artificial intelligence,Human-in-the-loop,Sentence generation,Machine learning | Conference |
ISSN | Citations | PageRank |
2639-1589 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sathish K. Sankarpandi | 1 | 0 | 0.34 |
| Spyros Samothrakis | 2 | 0 | 0.34 |
| luca citi | 3 | 168 | 27.88 |
| Peter Brady | 4 | 0 | 0.34 |