1,118 research outputs found
ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly
Matrix completion and approximation are popular tools to capture a user's
preferences for recommendation and to approximate missing data. Instead of
using low-rank factorization we take a drastically different approach, based on
the simple insight that an additive model of co-clusterings allows one to
approximate matrices efficiently. This allows us to build a concise model that,
per bit of model learned, significantly beats all factorization approaches to
matrix approximation. Even more surprisingly, we find that summing over small
co-clusterings is more effective in modeling matrices than classic
co-clustering, which uses just one large partitioning of the matrix.
Following Occam's razor principle suggests that the simple structure induced
by our model better captures the latent preferences and decision making
processes present in the real world than classic co-clustering or matrix
factorization. We provide an iterative minimization algorithm, a collapsed
Gibbs sampler, theoretical guarantees for matrix approximation, and excellent
empirical evidence for the efficacy of our approach. We achieve
state-of-the-art results on the Netflix problem with a fraction of the model
complexity.Comment: 22 pages, under review for conference publicatio
Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates
The privacy-sensitive nature of decentralized datasets and the robustness of
eXtreme Gradient Boosting (XGBoost) on tabular data raise the needs to train
XGBoost in the context of federated learning (FL). Existing works on federated
XGBoost in the horizontal setting rely on the sharing of gradients, which
induce per-node level communication frequency and serious privacy concerns. To
alleviate these problems, we develop an innovative framework for horizontal
federated XGBoost which does not depend on the sharing of gradients and
simultaneously boosts privacy and communication efficiency by making the
learning rates of the aggregated tree ensembles learnable. We conduct extensive
evaluations on various classification and regression datasets, showing our
approach achieves performance comparable to the state-of-the-art method and
effectively improves communication efficiency by lowering both communication
rounds and communication overhead by factors ranging from 25x to 700x.Comment: Accepted at the 3rd ACM Workshop on Machine Learning and Systems
(EuroMLSys), May 8th 2023, Rome, Ital
Detector for imaging of explosions: present status and future prospects with higher energy X-rays
The detector for imaging of explosions (DIMEX) is in operation at the
synchrotron radiation (SR) beam-line at VEPP-3 electron ring at Budker INP
since 2002. DIMEX is based on one-coordinate gas ionization chamber filled with
Xe-CO2(3:1) mixture at 7atm, and active Frisch-grid made of Gas Electron
Multiplier (GEM). The detector has spatial resolution of ~0.2mm and dynamic
range of ~100 that allows to realize the precision of signal measurement at a
percent level. The frame rate can be tuned up to 8 MHz (125 ns per image) and
up to 32 images can be stored in one shot. At present DIMEX is used with the
X-ray beam from 2T wiggler that has ~20 keV average energy. Future possibility
to install similar detector at the SR beam-line at VEPP-4 electron ring is
discussed.Comment: 14 pages, 15 figures. Submitted to JINS
Extensive collection of femtoliter pad secretion droplets in beetle Leptinotarsa decemlineata allows nanoliter microrheology
Pads of beetles are covered with long, deformable setae, each ending in a
micrometric terminal plate coated with secretory fluid. It was recently shown
that the layer of the pad secretion covering the terminal plates is responsible
for the generation of strong attractive forces. However, less is known about
the fluid itself because it is produced in extremely small quantity. We here
present a first experimental investigation of the rheological properties of the
pad secretion in the Colorado potato beetle {\it Leptinotarsa decemlineata}.
Because the secretion is produced in an extremely small amount at the level of
the terminal plate, we first develop a procedure based on capillary effects to
collect the secretion. We then manage to incorporate micrometric beads,
initially in the form of a dry powder, and record their thermal motion to
determine the mechanical properties of the surrounding medium. We achieve such
a quantitative measurement within the collected volume, much smaller than the
l sample volume usually required for this technique. Surprisingly,
the beetle secretion was found to behave as a purely viscous liquid, of high
viscosity. This suggests that no specific complex fluid behaviour is needed
during beetle locomotion. We build a scenario for the contact formation between
the spatula at the setal tip and a substrate, during the insect walk. We show
that the attachment dynamics of the insect pad computed from the high measured
viscosity is in good agreement with observed insect pace. We finally discuss
the consequences of the secretion viscosity on the insect adhesion
Stock Price Booms and Expected Capital Gains
Investors' subjective capital gains expectations are a key element explaining stock price fluctuations. Survey measures of these expectations display excessive optimism (pessimism) at market peaks (troughs). We formally reject the hypothesis that this is compatible with rational expectations. We then incorporate subjective price beliefs with such properties into a standard asset-pricing model with rational agents (internal rationality). The model gives rise to boom-bust cycles that temporarily delink stock prices from fundamentals and quantitatively replicates many asset-pricing moments. In particular, it matches the observed strong positive correlation between the price dividend ratio and survey return expectations, which cannot be matched by rational expectations
Wonderfully weird: the head anatomy of the armadillo ant, Tatuidris tatusia (Hymenoptera: Formicidae: Agroecomyrmecinae), with evolutionary implications
Tatuidris tatusia Brown & Kempf, 1968, the armadillo ant, is a morphologically unique species found in low to high elevation forests in regions of Central and South America. It is one of only two extant representatives of the subfamily Agroecomyrmecinae, and very little is known about the biology of these ants, which are almost exclusively collected from leaf litter and have rarely been seen alive. Here, we illuminate the functional morphology and evolution of this species via detailed anatomical documentation of their exceptionally modified head. We describe and illustrate the skeletomuscular system, digestive tract, and cephalic glands based on high-resolution micro-computed tomography scan data. We hypothesize that the modifications which produce the unusual “shield-like” head shape are the result of complex optimizations for mandibular power, physical protection, and balance. The most conspicuous cephalic features are the broadening of the frontal region and foreshortening of the postgenal region. The former characteristic is likely also associated with the lateral position of the antennal scrobe, the inverted antennal articulation, and the broad attachment surface for the mandibular adductor muscles. This head geometry also comes with a degree of internal restructuring of the tentorium and the antennal musculature, which have a unique configuration among ants studied so far. The mandibular blades, and their articulations and muscles, are highly distinctive compared with previously evaluated species. Using a 3D-printed model, we were able to hypothesize their entire range of motion as the mandibles fit tightly into the oral foramen. Finally, we compare T. tatusia across other related subfamilies and discuss the evolution of the Agroecomyrmecinae and other species-poor and phylogenetically isolated “relictual” lineages.journal articl
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