3,295 research outputs found
The largest singletons in weighted set partitions and its applications
Recently, Deutsch and Elizalde studied the largest and the smallest fixed
points of permutations. Motivated by their work, we consider the analogous
problems in weighted set partitions. Let denote the total
weight of partitions on with the largest singleton . In this
paper, explicit formulas for and many combinatorial
identities involving are obtained by umbral operators and
combinatorial methods. As applications, we investigate three special cases such
as permutations, involutions and labeled forests. Particularly in the
permutation case, we derive a surprising identity analogous to the Riordan
identity related to tree enumerations, namely, \begin{eqnarray*}
\sum_{k=0}^{n}\binom{n}{k}D_{k+1}(n+1)^{n-k} &=& n^{n+1}, \end{eqnarray*} where
is the -th derangement number or the number of permutations of
with no fixed points.Comment: 15page
On Multi-Relational Link Prediction with Bilinear Models
We study bilinear embedding models for the task of multi-relational link
prediction and knowledge graph completion. Bilinear models belong to the most
basic models for this task, they are comparably efficient to train and use, and
they can provide good prediction performance. The main goal of this paper is to
explore the expressiveness of and the connections between various bilinear
models proposed in the literature. In particular, a substantial number of
models can be represented as bilinear models with certain additional
constraints enforced on the embeddings. We explore whether or not these
constraints lead to universal models, which can in principle represent every
set of relations, and whether or not there are subsumption relationships
between various models. We report results of an independent experimental study
that evaluates recent bilinear models in a common experimental setup. Finally,
we provide evidence that relation-level ensembles of multiple bilinear models
can achieve state-of-the art prediction performance
CSWA: Aggregation-Free Spatial-Temporal Community Sensing
In this paper, we present a novel community sensing paradigm -- {C}ommunity
{S}ensing {W}ithout {A}ggregation}. CSWA is designed to obtain the environment
information (e.g., air pollution or temperature) in each subarea of the target
area, without aggregating sensor and location data collected by community
members. CSWA operates on top of a secured peer-to-peer network over the
community members and proposes a novel \emph{Decentralized Spatial-Temporal
Compressive Sensing} framework based on \emph{Parallelized Stochastic Gradient
Descent}. Through learning the \emph{low-rank structure} via distributed
optimization, CSWA approximates the value of the sensor data in each subarea
(both covered and uncovered) for each sensing cycle using the sensor data
locally stored in each member's mobile device. Simulation experiments based on
real-world datasets demonstrate that CSWA exhibits low approximation error
(i.e., less than C in city-wide temperature sensing task and
units of PM2.5 index in urban air pollution sensing) and performs comparably to
(sometimes better than) state-of-the-art algorithms based on the data
aggregation and centralized computation.Comment: This paper has been accepted by AAAI 2018. First two authors are
equally contribute
Side-chain and backbone ordering in Homopolymers
In order to study the relation between backbone and side chain ordering in
proteins, we have performed multicanonical simulations of deka-peptide chains
with various side groups. Glu10, Gln10, Asp10, Asn10, and Lys10 were selected
to cover a wide variety of possible interactions between the side chains of the
monomers. All homopolymers undergo helix-coil transitions. We found that
peptides with long side chains that are capable of hydrogen bonding, i.e.
Glu10, and Gln10, exhibit a second transition at lower temperatures connected
with side chain ordering. This occurs in gas phase as well as in solvent,
although the character of the side chain structure is different in each case.
However, in polymers with short side chains capable of hydrogen bonding, i.e.
Asp10 and Asn10, side chain ordering takes place over a wide temperature range
and exhibits no phase transition like character. Moreover, non-backbone
hydrogen bonds show enhanced formation and fluctuations already at the
helix-coil transition temperature, indicating competition between side chain
and backbone hydrogen bond formation. Again, these results are qualitatively
independent of the environment. Side chain ordering in Lys10, whose side groups
are long and polar, also takes place over a wide temperature range and exhibits
no phase transition like character in both environments. Reasons for the
observed chain length threshold and consequences from these results for protein
folding are discussed.Comment: 12 pages,11 figure
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