Artificial intelligence publications

We report our first experiences with Leaving Flatland, an exploratory project that studies the key challenges of closing the loop between autonomous perception and action on challenging terrain.

This case study article describes the iterative design process of an adaptive, mixed-initiative calendaring tool with embedded artificial intelligence. 

We investigate prediction of users’ desktop activities in the Unix domain. We show that simple efficient many-class learning can perform well for action prediction, significantly improving over previously published results…

In the first part of the paper, we show that efficient many-class learning can perform well for action prediction in the Unix domain, significantly improving over previously published results

We describe a computational framework that models  spatial  structure along the genomic sequence simultaneously with the temporal evolutionary path structure across species and show how such models can be used to discover…

This special interest group provides a forum to examine the apparent gap between HCI and AI communities, to explore how intelligent technologies can enable novel interaction with computation.

Although we appreciate the many challenges facing the current NIH grant system and applaud attempts at reform, we believe that several of the changes planned will cause more harm than…

Recent EcoCyc developments include a new initiative to represent and curate all types of E. coli regulatory processes such as attenuation and regulation by small RNAs.

We first show that for an STN, these messages can be represented compactly as sub-STNs. We then present an efficient message passing scheme for computing the minimal constraints of an…

In this extended abstract we describe the motivation, design, deployment and evaluation of the Emma system.

In this work we develop a representation that naturally combines the power of both relational and hierarchical models in the form of Logical Hierarchical Hidden Markov Models (LoHiHMMs).