380 citations · 487 across the 16 of their papers we have counts for
4 papers · 1 filter
Learning to Predict from Textual Data
Kira Radinsky, Sagie Davidovich, Shaul Markovitch
Given a current news event, we tackle the problem of generating plausible predictions of future events it might cause. We present a new methodology for modeling and predicting such…
Online Speedup Learning for Optimal Planning
Carmel Domshlak, Erez Karpas, Shaul Markovitch
Domain-independent planning is one of the foundational areas in the field of Artificial Intelligence. A description of a planning task consists of an initial world state, a goal, a…
Wikipedia-based Semantic Interpretation for Natural Language Processing
Evgeniy Gabrilovich, Shaul Markovitch
Adequate representation of natural language semantics requires access to vast amounts of common sense and domain-specific world knowledge. Prior work in the field was based on pure…
Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach
Saher Esmeir, Shaul Markovitch
Machine learning techniques are gaining prevalence in the production of a wide range of classifiers for complex real-world applications with nonuniform testing and misclassificatio…