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Robust Regression via Online Feature Selection under Adversarial Data Corruption
The presence of data corruption in user-generated streaming data, such as social media, motivates a new fundamental problem that learns reliable regression coefficient when features are not accessible entirely at one time.
Multimodal Storytelling via Generative Adversarial Imitation Learning
Deriving event storylines is an effective summarization method to succinctly organize extensive information, which can significantly alleviate the pain of information overload.
Online and Distributed Robust Regressions under Adversarial Data Corruption
In today's era of big data, robust least-squares regression becomes a more challenging problem when considering the adversarial corruption along with explosive growth of datasets.
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