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 $1 {\rm \mu}$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