Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
We study a model that incorporates a budget constraint in a decision making problem. Our goal is to maximize the expected wealth, where in each time period we can either stop the ...
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
—Dynamic resource allocation has the potential to provide significant increases in total revenue in enterprise systems through the reallocation of available resources as the dem...