1,116 research outputs found
Probing New Physics with b to s l l and b to s nu nu transitions
The rare decay B to K* (to K pi) mu+ mu- is regarded as one of the crucial
channels for B physics since its angular distribution gives access to many
observables that offer new important tests of the Standard Model and its
extensions. We point out a number of correlations among various observables
which will allow a clear distinction between different New Physics (NP)
scenarios. Furthermore, we discuss the decay B to K* nu anti-nu which allows
for a transparent study of Z penguin effects in NP frameworks in the absence of
dipole operator contributions and Higgs penguin contributions. We study all
possible observables in B to K* nu anti-nu and the related b to s transitions B
to K nu anti-nu and B to X_s nu anti-nu in the context of the SM and various NP
models.Comment: 4 pages, 2 figures, to appear in the proceedings of SUSY 09, 6-10
June 2009, Northeastern University, Bosto
Distantly Labeling Data for Large Scale Cross-Document Coreference
Cross-document coreference, the problem of resolving entity mentions across
multi-document collections, is crucial to automated knowledge base construction
and data mining tasks. However, the scarcity of large labeled data sets has
hindered supervised machine learning research for this task. In this paper we
develop and demonstrate an approach based on ``distantly-labeling'' a data set
from which we can train a discriminative cross-document coreference model. In
particular we build a dataset of more than a million people mentions extracted
from 3.5 years of New York Times articles, leverage Wikipedia for distant
labeling with a generative model (and measure the reliability of such
labeling); then we train and evaluate a conditional random field coreference
model that has factors on cross-document entities as well as mention-pairs.
This coreference model obtains high accuracy in resolving mentions and entities
that are not present in the training data, indicating applicability to
non-Wikipedia data. Given the large amount of data, our work is also an
exercise demonstrating the scalability of our approach.Comment: 16 pages, submitted to ECML 201
Query-Driven Sampling for Collective Entity Resolution
Probabilistic databases play a preeminent role in the processing and
management of uncertain data. Recently, many database research efforts have
integrated probabilistic models into databases to support tasks such as
information extraction and labeling. Many of these efforts are based on batch
oriented inference which inhibits a realtime workflow. One important task is
entity resolution (ER). ER is the process of determining records (mentions) in
a database that correspond to the same real-world entity. Traditional pairwise
ER methods can lead to inconsistencies and low accuracy due to localized
decisions. Leading ER systems solve this problem by collectively resolving all
records using a probabilistic graphical model and Markov chain Monte Carlo
(MCMC) inference. However, for large datasets this is an extremely expensive
process. One key observation is that, such exhaustive ER process incurs a huge
up-front cost, which is wasteful in practice because most users are interested
in only a small subset of entities. In this paper, we advocate pay-as-you-go
entity resolution by developing a number of query-driven collective ER
techniques. We introduce two classes of SQL queries that involve ER operators
--- selection-driven ER and join-driven ER. We implement novel variations of
the MCMC Metropolis Hastings algorithm to generate biased samples and
selectivity-based scheduling algorithms to support the two classes of ER
queries. Finally, we show that query-driven ER algorithms can converge and
return results within minutes over a database populated with the extraction
from a newswire dataset containing 71 million mentions
Commutators in the Two-Weight Setting
Let be the vector of Riesz transforms on , and let
be two weights on , . The
two-weight norm inequality for the commutator is shown to be equivalent to the function
being in a BMO space adapted to and . This is a common extension
of a result of Coifman-Rochberg-Weiss in the case of both and
being Lebesgue measure, and Bloom in the case of dimension one.Comment: v3: suggestions from two referees incorporate
Multiparameter Riesz Commutators
It is shown that product BMO of Chang and Fefferman, defined on the product
of Euclidean spaces can be characterized by the multiparameter commutators of
Riesz transforms. This extends a classical one-parameter result of Coifman,
Rochberg, and Weiss, and at the same time extends the work of Lacey and
Ferguson and Lacey and Terwilleger on multiparameter commutators with Hilbert
transforms. The method of proof requires the real-variable methods throughout,
which is new in the multi-parameter context.Comment: 38 Pages. References updated. To appear in American J Mat
Multi-Parameter Div-Curl Lemmas
We study the possible analogous of the Div-Curl Lemma in classical harmonic
analysis and partial differential equations, but from the point of view of the
multi-parameter setting. In this context we see two possible Div-Curl lemmas
that arise. Extensions to differential forms are also given.Comment: v1: 8 page
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