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Multistrategy Learning Methods for Multirobot Systems
(Georgia Institute of Technology, 2003)
This article describes three different methods for introducing machine learning into a hybrid deliberative/reactive architecture for multirobot systems: learning momentum, Q-learning, and CBR wizards. A range of simulation ...
Empirically-based self-diagnosis and repair of domain knowledge
(Georgia Institute of Technology, 2009-12-17)
In this work, I view incremental experiential learning in intelligent software agents as progressive agent self-adaptation. When an agent produces an incorrect behavior, then it may reflect on, and thus diagnose and repair, ...
The Contextual Bandits Problem: Techniques for Learning to Make High-Reward Decisions
(2017-10-30)
We consider how to learn through experience to make intelligent decisions. In the generic setting, called the contextual bandits problem, the learner must repeatedly decide which action to take in response to an observed ...
The Complexity of Learning Neural Networks
(2017-10-30)
The empirical successes of neural networks currently lack rigorous theoretical explanation. A first step might be to show that data generated by neural networks with a single hidden layer, smooth activation functions and ...
Novel document representations based on labels and sequential information
(Georgia Institute of Technology, 2015-07-23)
A wide variety of text analysis applications are based on statistical machine learning techniques. The success of those applications is critically affected by how we represent a document. Learning an efficient document ...
Recognizing Water-Based Activities in the Home Through Infrastructure-Mediated Sensing
(Georgia Institute of Technology, 2012-09)
Activity recognition in the home has been long recognized as
the foundation for many desirable applications in fields such
as home automation, sustainability, and healthcare. However,
building a practical home activity ...
Inferring Meal Eating Activities in Real World Settings from Ambient Sounds: A Feasibility Study
(Georgia Institute of Technology, 2015)
Dietary self-monitoring has been shown to be an effective method for weight-loss, but it remains an onerous task despite recent advances in food journaling systems. Semi-automated food journaling can reduce the effort of ...
Modeling Rich Structured Data via Kernel Distribution Embeddings
(Georgia Institute of Technology, 2011-03-25)
Real world applications often produce a large volume of highly uncertain and complex data. Many of them have rich microscopic structures where each variable can take values on manifolds (e.g., camera rotations), combinatorial ...
Towards tighter integration of machine learning and discrete optimization
(Georgia Institute of Technology, 2019-03-28)
Discrete Optimization algorithms underlie intelligent decision-making in a wide variety of domains. From airline fleet scheduling to data center resource management and matching in ride-sharing services, decisions are often ...
Manipulating state space distributions for sample-efficient imitation-learning
(Georgia Institute of Technology, 2020-03-16)
Imitation learning has emerged as one of the most effective approaches to train agents to act intelligently in unstructured and unknown domains. On its own or in combination with reinforcement learning, it enables agents ...