11,984 research outputs found
New Physics Searches with Photons in CDF
A brief review of searches for physics beyond the Standard Model with photons
using the CDF detector at the Tevatron is given here. These include searches
for supersymmetry, extra dimensions, excited electrons and W/Z
production, as well as anomalous photon production. Recent results from CDF Run
II experiment is presented, but some results from Run I are also reviewed.Comment: To appear in the Proceedings of SUSY 2003, held at the University of
Arizona, Tucson, AZ, 5-10 June 200
Searches for Physics Beyond the Standard Model at CMS
Recent results on searches for physics beyond the Standard Model at Large
Hadron Collider are presented, based on early LHC data in proton-proton
collisions at TeV collected by the CMS experiment. Prospects of
early SUSY searches at CMS are also outlined.Comment: 6 pages, Proceedings of Hadron Collider Physics Symposium, HCP 2010,
Toront
Democratization, autocratization, and coups: Assessing the impact of regime changes on forced migration:(Alternative Format Thesis)
Monte Carlo Bayesian Reinforcement Learning
Bayesian reinforcement learning (BRL) encodes prior knowledge of the world in
a model and represents uncertainty in model parameters by maintaining a
probability distribution over them. This paper presents Monte Carlo BRL
(MC-BRL), a simple and general approach to BRL. MC-BRL samples a priori a
finite set of hypotheses for the model parameter values and forms a discrete
partially observable Markov decision process (POMDP) whose state space is a
cross product of the state space for the reinforcement learning task and the
sampled model parameter space. The POMDP does not require conjugate
distributions for belief representation, as earlier works do, and can be solved
relatively easily with point-based approximation algorithms. MC-BRL naturally
handles both fully and partially observable worlds. Theoretical and
experimental results show that the discrete POMDP approximates the underlying
BRL task well with guaranteed performance.Comment: Appears in Proceedings of the 29th International Conference on
Machine Learning (ICML 2012
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