Deep Unsupervised Similarity Learning using Partially Ordered Sets

Unsupervised learning of visual similarities is of paramount importance to computer vision, particularly due to lacking training data for fine-grained similarities. Deep learning of similarities is often based on relationships between pairs or triplets of samples. Many of these relations are unreliable and mutually contradicting, implying inconsistencies when trained without supervision information that relates different tuples or triplets to each other. To overcome this problem, we use local estimates of reliable (dis-)similarities to initially group samples into compact surrogate classes and use local partial orders of samples to classes to link classes to each other. Similarity learning is then formulated as a partial ordering task with soft correspondences of all samples to classes. Adopting a strategy of self-supervision, a CNN is trained to optimally represent samples in a mutually consistent manner while updating the classes. The similarity learning and grouping procedure are integrated in a single model and optimized jointly. The proposed unsupervised approach shows competitive performance on detailed pose estimation and object classification.Comment: Accepted for publication at IEEE Computer Vision and Pattern Recognition 201

Electron-Ion Recombination Rate Coefficients and Photoionization Cross Sections for Astrophysically Abundant Elements VI. Ni II

We present the first detailed ab initio quantum mechanical calculations for total and state-specific recombination rate coefficients for e + Ni III --> Ni II. These rates are obtained using a unified treatment for total electron-ion recombination that treats the nonresonant radiative recombination and the resonant dielectronic recombination in a self-consistent unified manner in the close coupling approximation. Large-scale calculations are carried out using a 49-state wavefunction expansion from core configurations 3d^8, 3d^74s, and 3d^64p that permits the inclusion of prominent dipole allowed core transitions. These extensive calculations for the recombination rates of Ni II required hundreds of CPU hours on the Cray T90. The total recombination rate coefficients are provided for a wide range of temperature. The state-specific recombination rates for 532 bound states of doublet and quartet symmetries, and the corresponding photoionization cross sections for leaving the core in the ground state, are presented. Present total recombination rate coefficients differ considerably from the currently used data in astrophysical models.Comment: ApJ Suppl. (submitted), 4 figure