Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Learning with Drift Detection
Learning in the presence of concept drift and hidden contexts
OLINDDA: a cluster-based approach for detecting novelty and concept drift in data streams
Online anomaly detection with concept drift adaptation using recurrent neural networks
Active Learning With Drifting Streaming Data
Drift Analysis and Evolutionary Algorithms Revisited
Mining Recurring Concept Drifts with Limited Labeled Streaming Data
An ensemble classification approach for handling spatio-temporal drifts in partially labeled data streams
A review on real time data stream classification and adapting to various concept drift scenarios
Prequential AUC: properties of the area under the ROC curve for data streams with concept drift
Fast and Accurate Business Process Drift Detection
A Drifting-Games Analysis for Online Learning and Applications to Boosting
Optimal detection of changepoints with a linear computational cost
Scalable real-time classification of data streams with concept drift
Distribution Driven Extraction and Tracking of Features for Time-varying Data Analysis
New evolving ensemble classifier for handling concept drifting data streams
Domain Adaptation Extreme Learning Machines for Drift Compensation in E-nose Systems
Correcting Sensor Drift and Intermittency Faults With Data Fusion and Automated Learning
Efficient handling of concept drift and concept evolution over Stream Data
DDD: A New Ensemble Approach for Dealing with Concept Drift
Classification and Novel Class Detection in Concept-Drifting Data Streams under Time Constraints
Edge-adaptive transforms for efficient depth map coding
Paraphrasing Out-of-Vocabulary Words with Word Embeddings and Semantic Lexicons for Low Resource Statistical Machine Translation.
Hypertension in rheumatoid arthritis
TensorLog: Deep Learning Meets Probabilistic DBs
Queries and Concept Learning