On the Equivalence Between Deep NADE and Generative Stochastic Networks

Neural Autoregressive Distribution Estimators (NADEs) have recently been shown as successful alternatives for modeling high dimensional multimodal distributions. One issue associated with NADEs is that they rely on a particular order of factorization for $P(\mathbf{x})$. This issue has been recently addressed by a variant of NADE called Orderless NADEs and its deeper version, Deep Orderless NADE. Orderless NADEs are trained based on a criterion that stochastically maximizes $P(\mathbf{x})$ with all possible orders of factorizations. Unfortunately, ancestral sampling from deep NADE is very expensive, corresponding to running through a neural net separately predicting each of the visible variables given some others. This work makes a connection between this criterion and the training criterion for Generative Stochastic Networks (GSNs). It shows that training NADEs in this way also trains a GSN, which defines a Markov chain associated with the NADE model. Based on this connection, we show an alternative way to sample from a trained Orderless NADE that allows to trade-off computing time and quality of the samples: a 3 to 10-fold speedup (taking into account the waste due to correlations between consecutive samples of the chain) can be obtained without noticeably reducing the quality of the samples. This is achieved using a novel sampling procedure for GSNs called annealed GSN sampling, similar to tempering methods that combines fast mixing (obtained thanks to steps at high noise levels) with accurate samples (obtained thanks to steps at low noise levels).Comment: ECML/PKDD 201

Context-aware Mission Control for Astronaut-Robot Collaboration

Space robot assistants are envisaged as semi-autonomous co-workers deployed to lighten the workload of astronauts in cumbersome and dangerous situations. In view of this, this work considers the prospects on the technology requirements for future space robot operations, by presenting a novel mission control concept for close astronaut-robot collaboration. A decentralized approach is proposed, in which an astronaut is put in charge of commanding the robot, and a mission control center on Earth maintains a list of authorized robot actions by applying symbolic, geometric, and context-specific filters. The concept is applied to actual space robot operations within the METERON SUPVIS Justin experiment. In particular, it is shown how the concept is utilized to guide an astronaut aboard the ISS in its mission to survey and maintain a solar panel farm in a simulated Mars environment

Derivation of Apollo 14 High-Al Basalts from Distinct Source Regions at Discrete Times: New Constraints

Apollo 14 basalts occur predominantly as clasts in breccias, but represent the oldest volcanic products that were returned from the Moon [1]. These basalts are relatively enriched in Al2O3 (11-16 wt%) compared to other mare basalts (7-11 wt%) and were originally classified into 5 compositional groups [2,3]. Neal et al. [4] proposed that a continuum of compositions existed. These were related through assimilation (of KREEP) and fractional crystallization (AFC). Age data, however, show that at least three volcanic episodes are recorded in the sample collection [1,5,6]. Recent work has demonstrated that there are three, possibly four groups of basalts in the Apollo 14 sample collection that were erupted from different source regions at different times [7]. This conclusion was based upon incompatible trace element (ITE) ratios of elements that should not be fractionated from one another during partial melting (Fig. 1). These groups are defined as Group A (Groups 4 & 5 of [3]), Group B (Groups 1 & 2 of [3]), and Group C (Group 3 of [3]). Basalt 14072 is distinct from Groups A-C

Fast Differentially Private Matrix Factorization

Differentially private collaborative filtering is a challenging task, both in terms of accuracy and speed. We present a simple algorithm that is provably differentially private, while offering good performance, using a novel connection of differential privacy to Bayesian posterior sampling via Stochastic Gradient Langevin Dynamics. Due to its simplicity the algorithm lends itself to efficient implementation. By careful systems design and by exploiting the power law behavior of the data to maximize CPU cache bandwidth we are able to generate 1024 dimensional models at a rate of 8.5 million recommendations per second on a single PC

Non-equilibrium Relations for Spin Glasses with Gauge Symmetry

We study the applications of non-equilibrium relations such as the Jarzynski equality and fluctuation theorem to spin glasses with gauge symmetry. It is shown that the exponentiated free-energy difference appearing in the Jarzynski equality reduces to a simple analytic function written explicitly in terms of the initial and final temperatures if the temperature satisfies a certain condition related to gauge symmetry. This result is used to derive a lower bound on the work done during the non-equilibrium process of temperature change. We also prove identities relating equilibrium and non-equilibrium quantities. These identities suggest a method to evaluate equilibrium quantities from non-equilibrium computations, which may be useful to avoid the problem of slow relaxation in spin glasses.Comment: 8 pages, 2 figures, submitted to JPS

Sampling constrained probability distributions using Spherical Augmentation

Statistical models with constrained probability distributions are abundant in machine learning. Some examples include regression models with norm constraints (e.g., Lasso), probit, many copula models, and latent Dirichlet allocation (LDA). Bayesian inference involving probability distributions confined to constrained domains could be quite challenging for commonly used sampling algorithms. In this paper, we propose a novel augmentation technique that handles a wide range of constraints by mapping the constrained domain to a sphere in the augmented space. By moving freely on the surface of this sphere, sampling algorithms handle constraints implicitly and generate proposals that remain within boundaries when mapped back to the original space. Our proposed method, called {Spherical Augmentation}, provides a mathematically natural and computationally efficient framework for sampling from constrained probability distributions. We show the advantages of our method over state-of-the-art sampling algorithms, such as exact Hamiltonian Monte Carlo, using several examples including truncated Gaussian distributions, Bayesian Lasso, Bayesian bridge regression, reconstruction of quantized stationary Gaussian process, and LDA for topic modeling.Comment: 41 pages, 13 figure

MicroRNA29a regulates IL-33-mediated tissue remodelling in tendon disease

MicroRNA (miRNA) has the potential for cross-regulation and functional integration of discrete biological processes during complex physiological events. Utilizing the common human condition tendinopathy as a model system to explore the cross-regulation of immediate inflammation and matrix synthesis by miRNA we observed that elevated IL-33 expression is a characteristic of early tendinopathy. Using in vitro tenocyte cultures and in vivo models of tendon damage, we demonstrate that such IL-33 expression plays a pivotal role in the transition from type 1 to type 3 collagen (Col3) synthesis and thus early tendon remodelling. Both IL-33 effector function, via its decoy receptor sST2, and Col3 synthesis are regulated by miRNA29a. Downregulation of miRNA29a in human tenocytes is sufficient to induce an increase in Col3 expression. These data provide a molecular mechanism of miRNA-mediated integration of the early pathophysiologic events that facilitate tissue remodelling in human tendon after injury

Star Formation and AGN in the Core of the Shapley Supercluster: A VLA Survey of A3556, A3558, SC1327-312, SC1329-313, and A3562

The core of the Shapley supercluster (A3556, A3558, SC1327-312, SC1329-313, and A3562) is an ideal region in which to study the effects of cluster mergers on the activity of individual galaxies. This paper presents the most comprehensive radio continuum investigation of the region, relying on a 63-pointing mosaic obtained with the Very Large Array yielding an areal coverage of nearly 7 square degrees. The mosaic provides a typical sensitivity of about 80 uJy at a resolution of 16", enabling detection of galaxies with star formation rates as low as 1 solar mass per year. The radio data are complemented by optical imaging in B and R, producing a catalog of 210 radio-detected galaxies with m_R <= 17.36 (M_R <= -19). At least 104 of these radio-detected galaxies are members of the supercluster on the basis of public velocity measurements. Across the entire core of the supercluster, there appears to be a significant deficit of radio galaxies at intermediate optical magnitudes (M_R between -21 and -22). This deficit is offset somewhat by an increase in the frequency with which brighter galaxies (M_R less than -22) host radio sources. More dramatic is the highly significant increase in the probability for fainter galaxies (M_R between -20 and -21) in the vicinity of A3562 and SC1329-313 to be associated with radio emission. The radio and optical data for these sources strongly suggest that these active galaxies are powered by star formation. In conjunction with recent X-ray analysis, this is interpreted as young starbursts related to the recent merger of SC1329-313 with A3562 and the rest of the supercluster.Comment: Accepted by AJ; 50 pages, including 16 figures (for full resolution PDF, see http://mywebpages.comcast.net/nealamiller2/Shapley_pp.pdf