7,696 research outputs found
Dimensionality reduction of clustered data sets
We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution of the model is an unsupervised generalisation of linear discriminant analysis. This provides a completely new approach to one of the most established and widely used classification algorithms. The performance of the model is then demonstrated on a number of real and artificial data sets
NLO QCD corrections to the production of a weak boson pair associated by a hard jet
In this talk we discuss recent progress concerning precise predictions for
the LHC. We give a status report of an application of the GOLEM method to deal
with multi-leg one-loop amplitudes, namely the next-to-leading order QCD
corrections to the process pp to V V + jet, where V is a weak boson W,Z.Comment: Talk at 2008 Rencontres de Moriond, QCD session, La Thuile, March
2007. Four page
Recommended from our members
Adding Carbon to the Equation in Online Flight Search
This study explores the potential to promote lower-emissions air travel by providing consumers with information about the carbon emissions of alternative flight choices in the context of online flight search and booking. Researchers surveyed over 450 UC Davis faculty, researchers, and staff, asking them to choose among hypothetical flight options for university-related business trips. Emissions estimates for flight alternatives were prominently displayed alongside cost, layovers and airport, and the lowest-emissions flight was labeled “Greenest Flight”. The researchers found an impressive rate of willingness to pay for lower-emissions flights: around 56,000 reduction in airfare costs, due to an increased willingness of travelers to take advantage of cheaper (often nonstop) flight options out of SFO. Broader university policies encouraging lower-emissions flights and enhanced public transportation within the multi-airport mega-region would likely support much greater carbon savings. Institutionalizing this “nudge” within organizations with large travel budgets, like the UC system, could have an industry-wide impact in aviation.View the NCST Project Webpag
Learning and Designing Stochastic Processes from Logical Constraints
Stochastic processes offer a flexible mathematical formalism to model and
reason about systems. Most analysis tools, however, start from the premises
that models are fully specified, so that any parameters controlling the
system's dynamics must be known exactly. As this is seldom the case, many
methods have been devised over the last decade to infer (learn) such parameters
from observations of the state of the system. In this paper, we depart from
this approach by assuming that our observations are {\it qualitative}
properties encoded as satisfaction of linear temporal logic formulae, as
opposed to quantitative observations of the state of the system. An important
feature of this approach is that it unifies naturally the system identification
and the system design problems, where the properties, instead of observations,
represent requirements to be satisfied. We develop a principled statistical
estimation procedure based on maximising the likelihood of the system's
parameters, using recent ideas from statistical machine learning. We
demonstrate the efficacy and broad applicability of our method on a range of
simple but non-trivial examples, including rumour spreading in social networks
and hybrid models of gene regulation
Factored expectation propagation for input-output FHMM models in systems biology
We consider the problem of joint modelling of metabolic signals and gene
expression in systems biology applications. We propose an approach based on
input-output factorial hidden Markov models and propose a structured
variational inference approach to infer the structure and states of the model.
We start from the classical free form structured variational mean field
approach and use a expectation propagation to approximate the expectations
needed in the variational loop. We show that this corresponds to a factored
expectation constrained approximate inference. We validate our model through
extensive simulations and demonstrate its applicability on a real world
bacterial data set
Verdi’s six-fours and la parola scenica
Verdi’s operas display many non-normative six-four chords. The question for the opera analyst, however, is not only what occurs musically, but why it does. Is there a dramatic function being served by this mix of harmonic-intervallic instability? We discuss four types of non-normative six-fours in Verdi: the arrival, wonder, evasion, and dissolving. But, even as we individuate these types, we note that they are all similar in one regard: they are all linked to a crucial dramatic statement that Verdi termed la parola scenica, a textual-musical signal that makes a dramatic situation suddenly evident
The politics of intergovernmental deficits: Theory and evidence
The purpose of this paper is twofold. First, we present a model of decentralized fiscal policy-making where a "coordination failure" problem arises. Second, we make an effort in order to empirically test this approach by developing an empirical investigation based on the recent experience of two countries: Argentina and Great Britain.
Power Allocation in Two-Hop Amplify-and-Forward MIMO Relay Systems with QoS requirements
The problem of minimizing the total power consumption while satisfying
different quality-of-service (QoS) requirements in a two-hop multiple-input
multiple-output network with a single non-regenerative relay is considered. As
shown by Y. Rong in [1], the optimal processing matrices for both linear and
non-linear transceiver architectures lead to the diagonalization of the
source-relay-destination channel so that the power minimization problem reduces
to properly allocating the available power over the established links.
Unfortunately, finding the solution of this problem is numerically difficult as
it is not in a convex form. To overcome this difficulty, existing solutions
rely on the computation of upper- and lower-bounds that are hard to obtain or
require the relaxation of the QoS constraints. In this work, a novel approach
is devised for both linear and non-linear transceiver architectures, which
allows to closely approximate the solutions of the non-convex power allocation
problems with those of convex ones easy to compute in closed-form by means of
multi-step procedures of reduced complexity. Computer simulations are used to
assess the performance of the proposed approach and to make comparisons with
alternatives
- …