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Filtering by: Committee Member Tadepalli, Prasad Date issued sim 2017-06-16

Machine learning methods for public policy : simulation, optimization, and visualization

Creator:

McGregor, Sean

Abstract:

Society faces many complex management problems, particularly in the area of shared public resources such as ecosystems. Existing decision making processes are often guided by personal experience and political ideology rather than state-of-the-art scientific understanding. This dissertation envisions a future in which multiple stakeholders are provided with computational tools for...

Resource Type:

Dissertation
Weakly Supervised Learning for Activity Recognition from Time Series Data

Creator:

Guan, Xinze

Abstract:

The thesis focuses on activity recognition from sensor data, which has spurred a great deal of interest due to its impact on health care and security. Previous work on activity recognition from multivariate time series data has mainly applied supervised learning techniques which require a high degree of annotation effort...

Resource Type:

Dissertation
Learning with Partial Supervision for Clustering and Classification

Creator:

Pei, Yuanli

Abstract:

In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...

Resource Type:

Dissertation