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Register a new userAutomatic differentiation in ML: Where we are and where we should be going
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Added by
Pascal Lamblin
Publication date
2018
fields
Informatics Engineering
and research's language is
English
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We review the current state of automatic differentiation (AD) for array programming in machine learning (ML), including the different approaches such as operator overloading (OO) and source transformation (ST) used for AD, graph-based intermediate representations for programs, and source languages. Based on these insights, we introduce a new graph-based intermediate representation (IR) which specifically aims to efficiently support fully-general AD for array programming. Unlike existing dataflow programming representations in ML frameworks, our IR naturally supports function calls, higher-order functions and recursion, making ML models easier to implement. The ability to represent closures allows us to perform AD using ST without a tape, making the resulting derivative (adjoint) program amenable to ahead-of-time optimization using tools from functional language compilers, and enabling higher-order derivatives. Lastly, we introduce a proof of concept compiler toolchain called Myia which uses a subset of Python as a front end.
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We review the status of searches for sterile neutrinos in the $sim 1$ eV range, with an emphasis on the latest results from short baseline oscillation experiments and how they fit within sterile neutrino oscillation models. We present global fit results to a three-active-flavor plus one-sterile-flavor model (3+1), where we find an improvement of $Delta chi^2=35$ for 3 additional parameters compared to a model with no sterile neutrino. This is a 5$sigma$ improvement, indicating that an effect that is like that of a sterile neutrino is highly preferred by the data. However we note that separate fits to the appearance and disappearance oscillation data sets within a 3+1 model do not show the expected overlapping allowed regions in parameter space. This tension leads us to explore two options: 3+2, where a second additional mass state is introduced, and a 3+1+decay model, where the $ u_4$ state can decay to invisible particles. The 3+1+decay model, which is also motivated by improving compatibility with cosmological observations, yields the larger improvement, with a $Delta chi^2=8$ for 1 additional parameter beyond the 3+1 model, which is a $2.6sigma$ improvement. Moreover the tension between appearance and disappearance experiments is reduced compared to 3+1, although disagreement remains. In these studies, we use a frequentist approach and also a Bayesean method of finding credible regions. With respect to this tension, we review possible problems with the global fitting method. We note multiple issues, including problems with reproducing the experimental results, especially in the case of experiments that do not provide adequate data releases. We discuss an unexpected 5 MeV excess, observed in the reactor flux energy spectrum, that may be affecting the oscillation interpretation of the short baseline reactor data. We emphasize the care that must be taken in mapping to the true neutrino energy in the case of oscillation experiments that are subject to multiple interaction modes and nuclear effects. We point to problems with the Parameter-Goodness-of-Fit test that is used to quantify the tension. Lastly, we point out that analyses presenting limits often receive less scrutiny that signals. While we provide a snapshot of the status of sterile neutrino searches today and global fits to their interpretation, we emphasize that this is a fast-moving field. We briefly review experiments that are expected to report new data in the immediate future. Lastly, we consider the 5-year horizon, where we propose that decay-at-rest neutrino sources are the best method of finally resolving the confusing situation.
Two steps phase shifting interferometry has been a hot topic in the recent years. We present a comparison study of 12 representative self--tunning algorithms based on two-steps phase shifting interferometry. We evaluate the performance of such algorithms by estimating the phase step of synthetic and experimental fringe patterns using 3 different normalizing processes: Gabor Filters Bank (GFB), Deep Neural Networks (DNNs) and Hilbert Huang Transform (HHT); in order to retrieve the background, the amplitude modulation and noise. We present the variants of state-of-the-art phase step estimation algorithms by using the GFB and DNNs as normalization preprocesses, as well as the use of a robust estimator such as the median to estimate the phase step. We present experimental results comparing the combinations of the normalization processes and the two steps phase shifting algorithms. Our study demonstrates that the quality of the retrieved phase from of two-step interferograms is more dependent of the normalizing process than the phase step estimation method.
The orbital angular momentum of quarks and gluons contributes significantly to the proton spin budget and attracted a lot of attention in the recent years, both theoretically and experimentally. We summarize the various definitions of parton orbital angular momentum together with their relations with parton distributions functions. In particular, we highlight current theoretical puzzles and give some prospects.
Observations from the two STEREO-spacecraft give us for the first time the possibility to use stereoscopic methods to reconstruct the 3D solar corona. Classical stereoscopy works best for solid objects with clear edges. Consequently an application of classical stereoscopic methods to the faint structures visible in the optically thin coronal plasma is by no means straight forward and several problems have to be treated adequately: 1.)First there is the problem of identifying one dimensional structures -e.g. active region coronal loops or polar plumes- from the two individual EUV-images observed with STEREO/EUVI. 2.) As a next step one has the association problem to find corresponding structures in both images. 3.) Within the reconstruction problem stereoscopic methods are used to compute the 3D-geometry of the identified structures. Without any prior assumptions, e.g., regarding the footpoints of coronal loops, the reconstruction problem has not one unique solution. 4.) One has to estimate the reconstruction error or accuracy of the reconstructed 3D-structure, which depends on the accuracy of the identified structures in 2D, the separation angle between the spacecraft, but also on the location, e.g., for east-west directed coronal loops the reconstruction error is highest close to the loop top. 5.) Eventually we are not only interested in the 3D-geometry of loops or plumes, but also in physical parameters like density, temperature, plasma flow, magnetic field strength etc. Helpful for treating some of these problems are coronal magnetic field models extrapolated from photospheric measurements, because observed EUV-loops outline the magnetic field. This feature has been used for a new method dubbed magnetic stereoscopy. As examples we show recent application to active region loops.
In this article we first review the past decade of efforts in detecting the missing baryons in the Warm Hot Intergalactic Medium (WHIM) and summarize the current state of the art by updating the baryon census and physical state of the detected baryons in the local Universe. We then describe observational strategies that should enable a significant step forward in the next decade, while waiting for the step-up in quality offered by future missions. In particular we design a multi-mega-second and multiple cycle XMM-Newton legacy program (which we name the Ultimate Roaming Baryon Exploration, or URBE) aimed to secure detections of the peaks in the density distribution of the Universe missing baryons over their entire predicted range of temperatures.
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