Information extraction systems usually require two dictionaries: a semantic lexicon and a dictionary of extraction patterns for the domain. We present a multilevel bootstrapping algorithm that generates both the semantic lexicon and extraction patterns simultaneously. As input, our technique requires only unannotated training texts and a handful of seed words for a category. We use a mutual boo...

Kriging or Gaussian process models are popular metamodels (surrogate emulators) of simulation models; these give predictors for input combinations that not simulated. To validate computationally expensive models, the analysts often apply efficient cross-validation. In this paper, we derive new statistical tests so-called leave-one-out Graphically, present as scatterplots augmented with confiden...

The proposed project involves the design and implementation of a novel computational model of simultaneous acquisition of two languages from birth, or bilingual first language acquisition (BFLA). More specifically, we explore computationally the theory of Phonological Bootstrapping (Christophe et al. 1994, Christophe and Dupoux 1996, Morgan and Demuth 1996, Christophe et al. 1997), working with...

The success of bootstrapping or replacing a human judge with a model (e.g., an equation) has been demonstrated in Paul Meehl's (1954) seminal work and bolstered by the results of several meta-analyses. To date, however, analyses considering different types of meta-analyses as well as the potential dependence of bootstrapping success on the decision domain, the level of expertise of the human ju...

As an important cryptographic primitive in cloud computing and outsourced computation, fully homomorphic encryption (FHE) is an animated area of modern cryptography. However, the efficiency of FHE has been a bottleneck that impeding its application. According to Gentry’s blueprint, bootstrapping, which is used to decrease ciphertext errors, is the most important process in FHE. However, bootstr...

Bootstrapping has been received a amount of attentions in many fields and achieved good results. While semantic lexicons also have been proved to be useful for many natural language processing tasks. This paper presents an approach to learn semantic lexicons using a new bootstrapping method which is based on Graph Mutual Reinforcement. The approach uses only unlabeled data and a few of seed wor...