Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Analyzing Sequence Data Based on Conditional Random Fields with Co-training
1 An Introduction to Conditional Random Fields for Relational Learning
Supervised Morphological Segmentation in a Low-Resource Learning Setting using Conditional Random Fields
Analyzing co-training style algorithms
Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression
Email classification with co-training
Deep-dense Conditional Random Fields for Object Co-segmentation
Semi-supervised Sequence Learning
Hybrid semi-Markov CRF for Neural Sequence Labeling
Dynamic Conditional Random Fields for Joint Sentence Boundary and Punctuation Prediction
Improving Conditional Sequence Generative Adversarial Networks by Stepwise Evaluation
Incorporating dictionary features into conditional random fields for gene/protein named entity recognition
Learning from Conditional Distributions via Dual Embeddings
Bidirectional LSTM-CRF Models for Sequence Tagging
Optimization, Maxent Models, And Conditional Estimation Without Magic
Structured Sequence Modeling with Graph Convolutional Recurrent Networks
A Fast Variational Approach for Learning Markov Random Field Language Models
Chinese Segmentation And New Word Detection Using Conditional Random Fields
Combining clustering and co-training to enhance text classification using unlabelled data
Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks
A brief survey on sequence classification
Finite-State Transducers In Language And Speech Processing
Visual Computing as a Key Enabling Technology for Industrie 4.0 and Industrial Internet
abordagem transacional para padroes de controle de fluxo de processos cientificos e de negocios .
Hebbian Learning of Context in Recurrent Neural Networks
What effect does distributed version control have on OSS project organization?