Large Scale Distributed Learning: Machine learning solutions for data distributed across different servers.
Learning with noisy and partially labeled data (few shot learning).
Time series prediction: fraud detection (automatically detecting documents whose content deviates from the collection of standard documents that they belong to), failure prediction (predictive maintenance), log / sequence analysis.
Automatic language processing: information retrieval and access, automatic text summarization, automatic text classification, multi-label classification.
Market and social media analysis: sentiment analysis (automatically extract feelings from a set of customer comments).
Analysis of raw and structured data.
Recommendation systems: prediction of user preference for different products (collaborative filtering).
