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Towards Algorithmic Accountability in Data Mining
Increasingly, machine learning and data mining techniques are being used in making crucial decisions in our daily lives ranging from credit card approvals to employment decisions. Despite the existing eﬀort of explaining ...
Scalable and Secure Learning with Limited Supervision over Data Streams
Applications that employ machine learning over a stream of data provide the knowledge necessary for its users to make informed decisions at the right time. With the advantages of cloud computing infrastructure, these ...
Novel Class Detection and Cross-Lingual Duplicate Detection over Online Data Stream
Data streams are continuous flows of data points. They are very common now-a-days in several domains such as e-commerce, education, health, security, and social networks. Their sheer volume and throughput speed pose a great ...
Bayesian Nonparametric Probabilistic Methods in Machine Learning
Many aspects of modern science, business and engineering have become data-centric, relying on tools from Artificial Intelligence and Machine Learning. Practitioners and researchers in these fields need tools that can ...
Robust Analysis of Non-Parametric Space-Time Clustering
Recently, the rampant growth of various remote sensing technologies has resulted in a spike of interest in space-time data mining and particularly clustering of environmental time series and spatio-temporal processes. ...