Anandeep S. Pannu and Katia Sycara The Robotics Institute School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 [email protected], [email protected] Abstract We describe a reusable agent that learns a model of the user's research interests for ltering conference announcements and request for proposals (RFPs) from the Web. For this task, there is a large volume of irrelevant ...

In this work, we propose a framework of learning with preferences, which combines some neurophysiological findings, prospect theory, and the classic reinforcement learning mechanism. Specifically, we extend the state representation of reinforcement learning with a multi-dimensional preference model controlled by an external state. This external state is designed to be independent from the reinf...

E-learning usability is a goal of the user centred elearning design. Its achievement depends on the determination of the requirements, characteristics and preferences of the users of an e-learning system or environment (learner, teacher and administrator of an educational process). This paper presents different aspects of e-learning usability. One of them requires an evaluation of learner’s pre...

In this paper, we review the framework of learning (from) label preferences, a particular instance of preference learning. Following an introduction to the learning setting, we particularly focus on our own work, which addresses this problem via the learning by pairwise comparison paradigm. From a machine learning point of view, learning by pairwise comparison is especially appealing as it deco...

Learning Temporal Preferences* We analyse households’ responses to an unanticipated change in consumption opportunities and evaluate their implications for the nature and formation of preferences. We study the tariff experiment conducted by South Central Bell where local telephone measured tariffs were introduced for the first time in Louisville, KY. Households were given the choice to remain i...

Selectional preference learning methods have usually focused on wordto-class relations, e.g., a verb selects as its subject a given nominal class. This papers extends previous statistical models to class-to-class preferences, and presents a model that learns selectional preferences for classes of verbs. The motivation is twofold: different senses of a verb may have different preferences, and so...

In this paper, we investigate a cooperative routing problem in time-varying Wireless Sensor Networks (WSNs) targeting the achievement of quality-of-service guarantees in delay and reliability domains. We develop a distributed adaptive cooperative routing protocol, called DACR, that exploits cooperative communication on top of delayand energyaware end-to-end routes and optimizes the trade-off be...

We present WASP-Bench: a novel approach to Word Sense Disambiguation, also providing a semi-automatic environment for a lexicographer to compose dictionary entries based on corpus evidence. For WSD, involving lexicographers tackles the twin obstacles to high accuracy: paucity of training data and insufficiently explicit dictionaries. For lexicographers, the computational environment fills the n...

The adoption level of emerging web technologies is on the rise in academic settings. However, a major obstacle in the practice of web-based instruction is the limited understanding of learners’ characteristics and perceptions about technology use. Thus there is a need to understand the relationship between students’ learning styles and their preferences for instructional strategies, including t...