Unsupervised Feature Learning through Divergent Discriminative Feature Accumulation

Unlike unsupervised approaches such as autoencoders that learn to reconstruct their inputs, this paper introduces an alternative approach to unsupervised feature learning called divergent discriminative feature accumulation (DDFA) that instead continually accumulates features that make novel discriminations among the training set. Thus DDFA features are inherently discriminative from the start even though they are trained without knowledge of the ultimate classification problem. Interestingly, DDFA also continues to add new features indefinitely (so it does not depend on a hidden layer size), is not based on minimizing error, and is inherently divergent instead of convergent, thereby providing a unique direction of research for unsupervised feature learning. In this paper the quality of its learned features is demonstrated on the MNIST dataset, where its performance confirms that indeed DDFA is a viable technique for learning useful features.Comment: Corrected citation formattin

Cloning and characterisation of a maize carotenoid cleavage dioxygenase (ZmCCD1) and its involvement in the biosynthesis of apocarotenoids with various roles in mutualistic and parasitic interactions

Colonisation of maize roots by arbuscular mycorrhizal (AM) fungi leads to the accumulation of apocarotenoids (cyclohexenone and mycorradicin derivatives). Other root apocarotenoids (strigolactones) are involved in signalling during early steps of the AM symbiosis but also in stimulation of germination of parasitic plant seeds. Both apocarotenoid classes are predicted to originate from cleavage of a carotenoid substrate by a carotenoid cleavage dioxygenase (CCD), but the precursors and cleavage enzymes are unknown. A Zea mays CCD (ZmCCD1) was cloned by RT-PCR and characterised by expression in carotenoid accumulating E. coli strains and analysis of cleavage products using GC¿MS. ZmCCD1 efficiently cleaves carotenoids at the 9, 10 position and displays 78% amino acid identity to Arabidopsis thaliana CCD1 having similar properties. ZmCCD1 transcript levels were shown to be elevated upon root colonisation by AM fungi. Mycorrhization led to a decrease in seed germination of the parasitic plant Striga hermonthica as examined in a bioassay. ZmCCD1 is proposed to be involved in cyclohexenone and mycorradicin formation in mycorrhizal maize roots but not in strigolactone formatio

Detecting extreme mass ratio inspirals with LISA using time-frequency methods II: search characterization

The inspirals of stellar-mass compact objects into supermassive black holes constitute some of the most important sources for LISA. Detection of these sources using fully coherent matched filtering is computationally intractable, so alternative approaches are required. In a previous paper (Wen and Gair 2005, gr-qc/0502100), we outlined a detection method based on looking for excess power in a time-frequency spectrogram of the LISA data. The performance of the algorithm was assessed using a single `typical' trial waveform and approximations to the noise statistics. In this paper we present results of Monte Carlo simulations of the search noise statistics and examine its performance in detecting a wider range of trial waveforms. We show that typical extreme mass ratio inspirals (EMRIs) can be detected at distances of up to 1--3 Gpc, depending on the source parameters. We also discuss some remaining issues with the technique and possible ways in which the algorithm can be improved.Comment: 15 pages, 9 figures, to appear in proceedings of GWDAW 9, Annecy, France, December 200

Emulating long-term synaptic dynamics with memristive devices

The potential of memristive devices is often seeing in implementing neuromorphic architectures for achieving brain-like computation. However, the designing procedures do not allow for extended manipulation of the material, unlike CMOS technology, the properties of the memristive material should be harnessed in the context of such computation, under the view that biological synapses are memristors. Here we demonstrate that single solid-state TiO2 memristors can exhibit associative plasticity phenomena observed in biological cortical synapses, and are captured by a phenomenological plasticity model called triplet rule. This rule comprises of a spike-timing dependent plasticity regime and a classical hebbian associative regime, and is compatible with a large amount of electrophysiology data. Via a set of experiments with our artificial, memristive, synapses we show that, contrary to conventional uses of solid-state memory, the co-existence of field- and thermally-driven switching mechanisms that could render bipolar and/or unipolar programming modes is a salient feature for capturing long-term potentiation and depression synaptic dynamics. We further demonstrate that the non-linear accumulating nature of memristors promotes long-term potentiating or depressing memory transitions

Summary of the 13th IACHEC Meeting

We summarize the outcome of the 13th meeting of the International Astronomical Consortium for High Energy Calibration (IACHEC), held at Tenuta dei Ciclamini (Avigliano Umbro, Italy) in April 2018. Fifty-one scientists directly involved in the calibration of operational and future high-energy missions gathered during 3.5 days to discuss the current status of the X-ray payload inter-calibration and possible approaches to improve it. This summary consists of reports from the various working groups with topics ranging from the identification and characterization of standard calibration sources, multi-observatory cross-calibration campaigns, appropriate and new statistical techniques, calibration of instruments and characterization of background, and communication and preservation of knowledge and results for the benefit of the astronomical community.Comment: 12 page

Calibrating and Stabilizing Spectropolarimeters with Charge Shuffling and Daytime Sky Measurements

Well-calibrated spectropolarimetry studies at resolutions of $R>$10,000 with signal-to-noise ratios (SNRs) better than 0.01\% across individual line profiles, are becoming common with larger aperture telescopes. Spectropolarimetric studies require high SNR observations and are often limited by instrument systematic errors. As an example, fiber-fed spectropolarimeters combined with advanced line-combination algorithms can reach statistical error limits of 0.001\% in measurements of spectral line profiles referenced to the continuum. Calibration of such observations is often required both for cross-talk and for continuum polarization. This is not straightforward since telescope cross-talk errors are rarely less than $\sim$1\%. In solar instruments like the Daniel K. Inouye Solar Telescope (DKIST), much more stringent calibration is required and the telescope optical design contains substantial intrinsic polarization artifacts. This paper describes some generally useful techniques we have applied to the HiVIS spectropolarimeter at the 3.7m AEOS telescope on Haleakala. HiVIS now yields accurate polarized spectral line profiles that are shot-noise limited to 0.01\% SNR levels at our full spectral resolution of 10,000 at spectral sampling of $\sim$100,000. We show line profiles with absolute spectropolarimetric calibration for cross-talk and continuum polarization in a system with polarization cross-talk levels of essentially 100\%. In these data the continuum polarization can be recovered to one percent accuracy because of synchronized charge-shuffling model now working with our CCD detector. These techniques can be applied to other spectropolarimeters on other telescopes for both night and day-time applications such as DKIST, TMT and ELT which have folded non-axially symmetric foci.Comment: Accepted to A&