We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
We develop an efficient incremental version of an existing cost-based filtering algorithm for the knapsack constraint. On a universe of n elements, m invocations of the algorith...
Irit Katriel, Meinolf Sellmann, Eli Upfal, Pascal ...
A new spectral approach to value function approximation has recently been proposed to automatically construct basis functions from samples. Global basis functions called proto-val...
This paper presents both a semantic and a computational model for multi-agent belief revision. We show that these two models are equivalent but serve different purposes. The seman...
We describe a point-based policy iteration (PBPI) algorithm for infinite-horizon POMDPs. PBPI replaces the exact policy improvement step of Hansen’s policy iteration with point...
Shihao Ji, Ronald Parr, Hui Li, Xuejun Liao, Lawre...
Lifted inference algorithms exploit repeated structure in probabilistic models to answer queries efficiently. Previous work such as de Salvo Braz et al.'s first-order variabl...
Brian Milch, Luke S. Zettlemoyer, Kristian Kerstin...
In the majority of cases, steel production constitutes the inception of the Supply Chains they are involved just as in automotive clusters or aerospace. Steel manufacturing compan...
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...