We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
The long-term goal of Project Halo is to build an application called Digital Aristotle that can answer questions on a variety of science topics and provide user and domain appropr...
Ken Barker, Vinay K. Chaudhri, Shaw Yi Chaw, Peter...
In artificial intelligence and pervasive computing research, inferring users' high-level goals from activity sequences is an important task. A major challenge in goal recogni...
The goal of our current research is machine learning with the help and guidance of a knowledge base (KB). Rather than learning numerical models, our approach generates explicit sy...
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
In this paper, we present a learning-based approach for enabling domain-awareness for a generic natural language interface. Our approach automatically acquires domain knowledge fr...
In this paper we develop a novel probabilistic model of computational trust that allows agents to exchange and combine reputation reports over heterogeneous, correlated multi-dime...
Steven Reece, Stephen Roberts, Alex Rogers, Nichol...
The popularity of current hand-held digital imaging devices such as camera phones, PDAs, camcorders has promoted the use of digital cameras to capture document images for daily in...
A mathematical programming formulation is proposed to eliminate irrelevant and redundant features for collaborative computer aided diagnosis which requires to detect multiple clin...