Related papers: Clan Structure Analysis and Rapidity Gap Probabili…
Optimization is widely used in statistics, and often efficiently delivers point estimates on useful spaces involving structural constraints or combinatorial structure. To quantify uncertainty, Gibbs posterior exponentiates the negative loss…
Previously it has been shown that some classes of mixing dynamical systems have limiting return times distributions that are almost everywhere Poissonian. Here we study the behaviour of return times at periodic points and show that the…
Emerging technologies are revealing the spiking activity in ever larger neural ensembles. Frequently, this spiking is far from independent, with correlations in the spike times of different cells. Understanding how such correlations impact…
It is well known that correlations in microarray data represent a serious nuisance deteriorating the performance of gene selection procedures. This paper is intended to demonstrate that the correlation structure of microarray data provides…
The parton momentum density distributions in the proton are determined from a next-to-leading order QCD analysis of structure functions measured at HERA and by fixed target experiments. Also included are data on the difference of the up and…
The success of recently proposed models for describing rapidity-gap events in DIS at HERA, in terms additional colour exchange between the struck system and the proton remnant in boson-gluon fusion events, are found to rely heavily on the…
We focus on the increasingly important area of sparse regression problems where there are many variables and the effects of a large subset of these are negligible. This paper describes the construction of hierarchical prior distributions…
In the framework of the weighted superposition mechanism of different classes of minimum bias events (or substructures), described by the negative binomial multiplicity distribution, in possible scenarios for pp collisions in the TeV energy…
The Generative Adversarial Networks (GAN) framework is a well-established paradigm for probability matching and realistic sample generation. While recent attention has been devoted to studying the theoretical properties of such models, a…
In this talk I review the low x QCD experimental results from HERA and their theoretical underpinnings. In particular, I discuss the structure function $F_2$, large rapidity gap events, pomeron structure functions and $J/\psi$ production.
We introduce a new class of latent process models for dynamic relational network data with the goal of detecting time-dependent structure. Network data are often observed over time, and static network models for such data may fail to…
Networks play a central role in modern data analysis, enabling us to reason about systems by studying the relationships between their parts. Most often in network analysis, the edges are given. However, in many systems it is difficult or…
We study a likelihood ratio test for detecting multiple {\it weak} changes in the mean of a class of CHARN models. The locally asymptotically normal (LAN) structure of the family of likelihoods under study is established. It results that…
Collaboration networks are studied as an example of growing bipartite networks. These have been previously observed to have structure such as positive correlations between nearest-neighbour degrees. However, a detailed understanding of the…
These proceedings outline steps toward a systematic analysis of frontier energy collider data: specifically, those data collected at Tevatron Runs I and II, LEP Run II, HERA Runs I and II, and the future LHC. Algorithms designed to…
After generalizing the concept of clusters to incorporate clusters that are linked to other clusters through some relatively narrow bridges, an approach for detecting patches of separation between these clusters is developed based on an…
A non-perturbative approach to Generalized Parton Distributions, and to Deeply Virtual Compton Scattering in particular, based on off mass shell extension of dual amplitudes with Mandelstam analyticity (DAMA) is developed with the spin and…
Empirical networks are often globally sparse, with a small average number of connections per node, when compared to the total size of the network. However, this sparsity tends not to be homogeneous, and networks can also be locally dense,…
A model of independent pair parton interactions is proposed, according to which, hadron interactions are represented by a set of independent binary parton collisions. The final multiplicity distribution is described by a convolution of the…
Categorical data are common in educational and social science research; however, methods for its analysis are generally not covered in introductory statistics courses. This chapter overviews fundamental concepts and methods in categorical…