We revisit from a modern bootstrap perspective the longstanding problem of solving QCD in large $N$ limit. derive universal bounds on effective field theory massless pions by imposing full set positivity constraints that follow $2 \to 2$ scattering. Some features our exclusion plots have intriguing connections with hadronic phenomenology. The boundary exhibits sharp kink, raising tantalizing sc...

This article proposes a new method for word translation disambiguation, one that uses a machinelearning technique called bilingual bootstrapping. In learning to disambiguate words to be translated, bilingual bootstrapping makes use of a small amount of classified data and a large amount of unclassified data in both the source and the target languages. It repeatedly constructs classifiers in the...

As the sizes of high-end computing systems continue to grow to massive scales, efficient bootstrapping for distributed software infrastructures is becoming a greater challenge. Distributed software infrastructure bootstrapping is the procedure of instantiating all processes of the distributed system on the appropriate hardware nodes and disseminating to these processes the information that they...

Iterative bootstrapping methods are widely employed for relation extraction, especially because they require only a small amount of human supervision. Unfortunately, a phenomenon known as semantic drift can affect the accuracy of iterative bootstrapping and lead to poor extractions. This paper proposes an alternative bootstrapping method, which ranks relation tuples by measuring their distance ...

We describe and contrast several different bootstrapping procedures for penalized spline smoothers. The bootstrapping procedures considered are variations on existing methods, developed under two different probabilistic frameworks. Under the first framework, penalized spline regression is considered an estimation technique to find an unknown smooth function. The smooth function is represented i...

The Weighted Histogram Analysis Method (WHAM) is a standard technique used to compute potentials of mean force (PMFs) from a set of umbrella sampling simulations. Here, we present a new WHAM implementation, termed g_wham, which is distributed freely with the GROMACS molecular simulation suite. g_wham estimates statistical errors using the technique of bootstrap analysis. Three bootstrap methods...