A Modern Take on the Bias-Variance Tradeoff in Neural Networks

The bias-variance tradeoff tells us that as model complexity increases, bias falls and variances increases, leading to a U-shaped test error curve. However, recent empirical results with over-parameterized neural networks are marked by a striking absence of the classic U-shaped test error curve: test error keeps decreasing in wider networks. This suggests that there might not be a bias-variance tradeoff in neural networks with respect to network width, unlike was originally claimed by, e.g., Geman et al. (1992). Motivated by the shaky evidence used to support this claim in neural networks, we measure bias and variance in the modern setting. We find that both bias and variance can decrease as the number of parameters grows. To better understand this, we introduce a new decomposition of the variance to disentangle the effects of optimization and data sampling. We also provide theoretical analysis in a simplified setting that is consistent with our empirical findings

Accretion, feedback and galaxy bimodality: a comparison of the GalICS semi-analytic model and cosmological SPH simulations

We compare the galaxy population of an SPH simulation to those predicted by the GalICS semi-analytic model and a stripped down version without supernova and AGN feedback. The SPH simulation and the no-feedback GalICS model make similar predictions for the baryonic mass functions of galaxies and for the dependence of these mass functions on environment and redshift. The two methods also make similar predictions for the galaxy content of dark matter haloes as a function of halo mass and for the gas accretion history of galaxies. Both the SPH and no-feedback GalICS models predict a bimodal galaxy population at z=0. The "red'' sequence of gas poor, old galaxies is populated mainly by satellite systems while, contrary to observations, the central galaxies of massive haloes lie on the "blue'' star-forming sequence as a result of continuing hot gas accretion at late times. Furthermore, both models overpredict the observed baryonic mass function, especially at the high mass end. In the full GalICS model, supernova-driven outflows reduce the masses of low and intermediate mass galaxies by about a factor of two. AGN feedback suppresses gas cooling in large haloes, producing a sharp cut-off in the baryonic mass function and moving the central galaxies of these massive haloes to the red sequence. Our results imply that the observational failings of the SPH simulation and the no-feedback GalICS model are a consequence of missing input physics rather than computational inaccuracies, that truncating gas accretion by satellite galaxies automatically produces a bimodal galaxy distribution with a red sequence, but that explaining the red colours of the most massive galaxies requires a mechanism like AGN feedback that suppresses the accretion onto central galaxies in large haloes.Comment: 17 pages, 11 figures, submitted to MNRA

Influence of grain size, shape and compaction on georadar waves: example of an Aeolian dune

Many Ground Penetrating Radar (GPR) profiles acquired in dry aeolian environment have shown good reflectivity inside present-day dunes. We show that the origin of this reflectivity is related to changes in grain size distribution, packing and/or grain shape in a sandy material. We integrate these three parameters into analytical models for bulk permittivity in order to predict the reflections and the velocity of GPR waves. We consider two GPR cross-sections acquired over Aeolian dunes in the Chadian desert. The 2D migration of GPR data suggests that dunes contain different kinds of bounding surfaces. We discuss and model three kinds of reflections using reasonable geological hypothesis about Aeolian sedimentation processes. The propagation and the reflection of radar waves are calculated using the 1D wavelet modelling method in spectral domain. The results of the forward modelling are in good accordance with real observed data

Non-parametric clustering over user features and latent behavioral functions with dual-view mixture models

International audienceWe present a dual-view mixture model to cluster users based on their features and latent behavioral functions. Every component of the mixture model represents a probability density over a feature view for observed user attributes and a behavior view for latent behavioral functions that are indirectly observed through user actions or behaviors. Our task is to infer the groups of users as well as their latent behavioral functions. We also propose a non-parametric version based on a Dirichlet Process to automatically infer the number of clusters. We test the properties and performance of the model on a synthetic dataset that represents the participation of users in the threads of an online forum. Experiments show that dual-view models outperform single-view ones when one of the views lacks information

Sequential Quasi-Monte Carlo

We derive and study SQMC (Sequential Quasi-Monte Carlo), a class of algorithms obtained by introducing QMC point sets in particle filtering. SQMC is related to, and may be seen as an extension of, the array-RQMC algorithm of L'Ecuyer et al. (2006). The complexity of SQMC is $O(N \log N)$, where $N$ is the number of simulations at each iteration, and its error rate is smaller than the Monte Carlo rate $O_P(N^{-1/2})$. The only requirement to implement SQMC is the ability to write the simulation of particle $x_t^n$ given $x_{t-1}^n$ as a deterministic function of $x_{t-1}^n$ and a fixed number of uniform variates. We show that SQMC is amenable to the same extensions as standard SMC, such as forward smoothing, backward smoothing, unbiased likelihood evaluation, and so on. In particular, SQMC may replace SMC within a PMCMC (particle Markov chain Monte Carlo) algorithm. We establish several convergence results. We provide numerical evidence that SQMC may significantly outperform SMC in practical scenarios.Comment: 55 pages, 10 figures (final version

Planet Hunters: The First Two Planet Candidates Identified by the Public using the Kepler Public Archive Data

Planet Hunters is a new citizen science project, designed to engage the public in an exoplanet search using NASA Kepler public release data. In the first month after launch, users identified two new planet candidates which survived our checks for false- positives. The follow-up effort included analysis of Keck HIRES spectra of the host stars, analysis of pixel centroid offsets in the Kepler data and adaptive optics imaging at Keck using NIRC2. Spectral synthesis modeling coupled with stellar evolutionary models yields a stellar density distribution, which is used to model the transit orbit. The orbital periods of the planet candidates are 9.8844 \pm0.0087 days (KIC 10905746) and 49.7696 \pm0.00039 (KIC 6185331) days and the modeled planet radii are 2.65 and 8.05 R\oplus. The involvement of citizen scientists as part of Planet Hunters is therefore shown to be a valuable and reliable tool in exoplanet detection.Comment: Submitted to MNRAS, added 1 line to table

ALMA Survey of Orion Planck Galactic Cold Clumps (ALMASOP) : Detection of Extremely High-density Compact Structure of Prestellar Cores and Multiple Substructures Within

Prestellar cores are self-gravitating dense and cold structures within molecular clouds where future stars are born. They are expected, at the stage of transitioning to the protostellar phase, to harbor centrally concentrated dense (sub)structures that will seed the formation of a new star or the binary/multiple stellar systems. Characterizing this critical stage of evolution is key to our understanding of star formation. In this work, we report the detection of high-density (sub)structures on the thousand-astronomical-unit (au) scale in a sample of dense prestellar cores. Through our recent ALMA observations toward the Orion Planck Galactic Cold Clumps, we have found five extremely dense prestellar cores, which have centrally concentrated regions of similar to 2000 au in size, and several 10(7) cm(-3) in average density. Masses of these centrally dense regions are in the range of 0.30 to 6.89 M. For the first time, our higher resolution observations (0.8 '' similar to 320 au) further reveal that one of the cores shows clear signatures of fragmentation; such individual substructures/fragments have sizes of 800-1700 au, masses of 0.08 to 0.84 M, densities of 2 - 8 x 10(7) cm(-3), and separations of similar to 1200 au. The substructures are massive enough (greater than or similar to 0.1 M) to form young stellar objects and are likely examples of the earliest stage of stellar embryos that can lead to widely (similar to 1200 au) separated multiple systems.Peer reviewe

Working with Language: A Refocused Research Agenda for Cultural Leadership Studies

© 2016 British Academy of Management and John Wiley & Sons Ltd This paper critically reviews existing contributions from the field of cultural leadership studies with a view to highlighting the conceptual and methodological limitations of the dominant etic, cross-cultural approach in leadership studies and illuminating implications of the relative dominance and unreflective use of the English language as the academic and business lingua franca within this field. It subsequently outlines the negative implications of overlooking cultural and linguistic multiplicity for an understanding of culturally sensitive leadership practices. In drawing on lessons from this critical review and the emergent fields of emic, non-positivist cultural leadership studies, this analysis argues that the field of cultural leadership studies requires an alternative research agenda focused on language multiplicity, which enables the field to move towards emic, qualitative research that helps to empower individual cultural voices and explore cultural intra- and interrelationships, tensions and paradoxes embedded in leadership processes. The paper concludes by offering suggestions on methodological approaches for emic cultural leadership studies that are centred on the exploration of language as a cultural voice