5,748 research outputs found
Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks
Can multilayer neural networks -- typically constructed as highly complex
structures with many nonlinearly activated neurons across layers -- behave in a
non-trivial way that yet simplifies away a major part of their complexities? In
this work, we uncover a phenomenon in which the behavior of these complex
networks -- under suitable scalings and stochastic gradient descent dynamics --
becomes independent of the number of neurons as this number grows sufficiently
large. We develop a formalism in which this many-neurons limiting behavior is
captured by a set of equations, thereby exposing a previously unknown operating
regime of these networks. While the current pursuit is mathematically
non-rigorous, it is complemented with several experiments that validate the
existence of this behavior
Time-lagged Ordered Lasso for network inference
Accurate gene regulatory networks can be used to explain the emergence of
different phenotypes, disease mechanisms, and other biological functions. Many
methods have been proposed to infer networks from gene expression data but have
been hampered by problems such as low sample size, inaccurate constraints, and
incomplete characterizations of regulatory dynamics. Since expression
regulation is dynamic, time-course data can be used to infer causality, but
these datasets tend to be short or sparsely sampled. In addition, temporal
methods typically assume that the expression of a gene at a time point depends
on the expression of other genes at only the immediately preceding time point,
while other methods include additional time points without any constraints to
account for their temporal distance. These limitations can contribute to
inaccurate networks with many missing and anomalous links.
We adapted the time-lagged Ordered Lasso, a regularized regression method
with temporal monotonicity constraints, for \textit{de novo} reconstruction. We
also developed a semi-supervised method that embeds prior network information
into the Ordered Lasso to discover novel regulatory dependencies in existing
pathways. We evaluated these approaches on simulated data for a repressilator,
time-course data from past DREAM challenges, and a HeLa cell cycle dataset to
show that they can produce accurate networks subject to the dynamics and
assumptions of the time-lagged Ordered Lasso regression
Semi-supervised network inference using simulated gene expression dynamics
Motivation: Inferring the structure of gene regulatory networks from
high--throughput datasets remains an important and unsolved problem. Current
methods are hampered by problems such as noise, low sample size, and incomplete
characterizations of regulatory dynamics, leading to networks with missing and
anomalous links. Integration of prior network information (e.g., from pathway
databases) has the potential to improve reconstructions.
Results: We developed a semi--supervised network reconstruction algorithm
that enables the synthesis of information from partially known networks with
time course gene expression data. We adapted PLS-VIP for time course data and
used reference networks to simulate expression data from which null
distributions of VIP scores are generated and used to estimate edge
probabilities for input expression data. By using simulated dynamics to
generate reference distributions, this approach incorporates previously known
regulatory relationships and links the network to the dynamics to form a
semi-supervised approach that discovers novel and anomalous connections. We
applied this approach to data from a sleep deprivation study with KEGG pathways
treated as prior networks, as well as to synthetic data from several DREAM
challenges, and find that it is able to recover many of the true edges and
identify errors in these networks, suggesting its ability to derive posterior
networks that accurately reflect gene expression dynamics
Interior gradient estimates for quasilinear elliptic equations
We study quasilinear elliptic equations of the form in bounded domains in
, . The vector field is allowed to be
discontinuous in , Lipschitz continuous in and its growth in the
gradient variable is like the -Laplace operator with . We
establish interior -estimates for locally bounded weak solutions to
the equations for every , and we show that similar results also hold true
in the setting of {\it Orlicz} spaces. Our regularity estimates extend results
which are only known for the case is independent of and they
complement the well-known interior - estimates obtained by
DiBenedetto \cite{D} and Tolksdorf \cite{T} for general quasilinear elliptic
equations
Smooth (non)rigidity of cusp-decomposable manifolds
We define cusp-decomposable manifolds and prove smooth rigidity within this
class of manifolds. These manifolds generally do not admit a nonpositively
curved metric but can be decomposed into pieces that are diffeomorphic to
finite volume, locally symmetric, negatively curved manifolds with cusps. We
prove that the group of outer automorphisms of the fundamental group of such a
manifold is an extension of an abelian group by a finite group. Elements of the
abelian group are induced by diffeomorphisms that are analogous to Dehn twists
in surface topology. We also prove that the outer automophism group can be
realized by a group of diffeomorphisms of the manifold.Comment: 13 pages, 1 figure. Accepted for publication in Comment. Math. Helv.
arXiv admin note: substantial overlap with arXiv:1105.520
Nil happens. What about Sol?
We construct complete, finite volume, 4-dimensional manifolds with sectional
curvature with cusp cross sections compact solvmanifolds.Comment: 2 page
Actions of higher rank, irreducible lattices on \CAT(0) cubical complexes
Let be an irreducible lattice of \Q-rank in a semisimple
Lie group of noncompact type. We prove that any action of on a
\CAT(0) cubical complex has a global fixed point.Comment: 5 pages, 1 figure. arXiv admin note: text overlap with
arXiv:1108.412
Minimal orbifolds and (a)symmetry of piecewise locally symmetric manifolds
We show that if is a Riemannian metric on a closed piecewise locally
symmetric manifold , then the lift of to the universal cover
has a discrete isometry group. We also show that the index
[\Isom(\widetilde{M}): \pi_1(M)] is bounded by a constant independent of .Comment: 8 pages, 2 figure
On finite volume, negatively curved manifolds
We study noncompact, complete, finite volume, negatively curved manifolds
. We construct with infinitely generated fundamental groups in all
dimensions . We construct whose cusp cross sections are compact
hyperbolic manifolds in all dimension . In contrast we show that if
sectional curvature , then cusp cross sections have zero simplicial
volume. We construct negatively curved lattices that do not contain any
parabolic isometries. We show that there are such that does
not satisfy the visibility axiom. We give a condition on the curvature growth
versus the volume decay that guarantees topological finiteness. We raise a few
questions on finite volume, negatively curved manifolds.Comment: 18 page
Gluing locally symmetric manifolds: asphericity and rigidity
We use the reflection group trick to glue manifolds with corners that are
Borel-Serre compactifications of locally symmetric spaces of noncompact type
and obtain aspherical manifolds. We call these \emph{piecewise locally
symmetric} manifolds. This class of spaces provide new examples of aspherical
manifolds whose fundamental groups have the structure of a complex of groups.
These manifolds typically do not admit a locally \CAT(0) metric. We prove
that any self homotopy equivalence of such manifolds is homotopic to a
homeomorphism. We compute the group of self homotopy equivalences of such a
manifold and show that it can contain a normal free abelian subgroup, and thus
can be infinite.Comment: 26 pages, 2 figure
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