Learning with Biased Complementary Labels

In this paper, we study the classification problem in which we have access to easily obtainable surrogate for true labels, namely complementary labels, which specify classes that observations do \textbf{not} belong to. Let $Y$ and $\bar{Y}$ be the true and complementary labels, respectively. We first model the annotation of complementary labels via transition probabilities $P(\bar{Y}=i|Y=j), i\neq j\in\{1,\cdots,c\}$, where $c$ is the number of classes. Previous methods implicitly assume that $P(\bar{Y}=i|Y=j), \forall i\neq j$, are identical, which is not true in practice because humans are biased toward their own experience. For example, as shown in Figure 1, if an annotator is more familiar with monkeys than prairie dogs when providing complementary labels for meerkats, she is more likely to employ "monkey" as a complementary label. We therefore reason that the transition probabilities will be different. In this paper, we propose a framework that contributes three main innovations to learning with \textbf{biased} complementary labels: (1) It estimates transition probabilities with no bias. (2) It provides a general method to modify traditional loss functions and extends standard deep neural network classifiers to learn with biased complementary labels. (3) It theoretically ensures that the classifier learned with complementary labels converges to the optimal one learned with true labels. Comprehensive experiments on several benchmark datasets validate the superiority of our method to current state-of-the-art methods.Comment: ECCV 2018 Ora

Many-body effects in the stimulated Raman response of binary mixtures:A comparison between theory and experiment

The subpicosecond dynamics of binary mixtures of carbon disulfide and alkane have been studied using third-order time-resolved Raman techniques. Both the anisotropic and the isotropic responses were investigated. These depend differently on many-body contributions to the first-order susceptibility and probe different modes in the liquid. The anisotropic response is dominated by single molecule effects, whereas the isotropic response is completely determined by many-body contributions since the single molecule response vanishes. To interpret the experimental results, molecular dynamics simulations were performed on model mixtures. The effect of dilution on the subpicosecond response cannot be explained by many-body effects in the first-order susceptibility alone. Aggregation due to permanent quadrupole moments on the carbon disulfide molecules and density changes upon dilution are also inadequate explanations for the observed effect. Apparently the character of the many-body dynamics itself is modified by the change of the molecular force fields, when carbon disulfide molecules are replaced by alkanes.<br/

Automatic cattle identification using graph matching based on local invariant features

Cattle muzzle classification can be considered as a biometric identifier important to animal traceability systems to ensure the integrity of the food chain. This paper presents a muzzle-based classification system that combines local invariant features with graph matching. The proposed approach consists of three phases; namely feature extraction, graph matching, and matching refinement. The experimental results showed that our approach is superior than existing works as ours achieves an all correct identification for the tested images. In addition, the results proved that our proposed method achieved this high accuracy even if the testing images are rotated in various angles.info:eu-repo/semantics/publishedVersio

The third- and fifth-order nonlinear Raman response of liquid CS2 calculated using a finite field nonequilibrium molecular dynamics method

A finite field molecular dynamics (MD) method has been developed to calculate the off-resonant Raman response of liquids. The method has been used to calculate the third- and fifth-order optical responses of CS2. From the third-order response, the intensity of third-order cascading processes has been estimated. The calculated ratio between the fifth-order intensity and the intensity of the third-order cascading processes supports experimental observations, claiming that two-dimensional Raman spectra are dominated by third-order cascading processes

Countdown to Annihilation: Genocide in Myanmar

This report analyses the persecution of the Rohingya against the six stages of genocide outlined by Daniel Feierstein: stigmatisation (and dehumanisation); harassment, violence and terror; isolation and segregation; systematic weakening; mass annihilation; and finally symbolic enactment involving the removal of the victim group from the collective history. The report concludes that the Rohingya have suffered the first four of the six stages of genocide. They have been, and continue to be, stigmatized, dehumanised and discriminated against. They have been harassed, terrorized and slaughtered. They have been isolated and segregated into detention camps and securitised villages and ghettos. They have been systematically weakened through hunger, illness, denial of civil rights and loss of livelihood. All of this places them at high risk of annihilation

Interaction induced effects in the nonlinear Raman response of liquid CS2:A finite field nonequilibrium molecular dynamics approach

The third- and fifth-order time-domain Raman responses of liquid carbon disulfide have been calculated, taking local field effects into account through the dipole-induced dipole approximation to the polarizability. The third-order response is shown to be in excellent agreement with experimental data. The calculated two-dimensional shape of the fifth-order response is compared with recently reported experimental observations of what is claimed to be pure fifth-order response. Considerable discrepancies are observed which might be explained by contamination of the experimental results with sequential and especially parallel third-order cascaded Raman response. A new choice of polarization conditions is proposed, which increases the discrimination against these unwanted cascading effects, as compared to the previously discussed fully polarized and magic angle conditions

Genomics-Based Identifcation of Microorganisms in Human Ocular Body Fluid

Abstract Advances in genomics have the potential to revolutionize clinical diagnostics. Here, we examine the microbiome of vitreous (intraocular body fluid) from patients who developed endophthalmitis following cataract surgery or intravitreal injection. Endophthalmitis is an inflammation of the intraocular cavity and can lead to a permanent loss of vision. As controls, we included vitreous from endophthalmitis-negative patients, balanced salt solution used during vitrectomy and DNA extraction blanks. We compared two DNA isolation procedures and found that an ultraclean production of reagents appeared to reduce background DNA in these low microbial biomass samples. We created a curated microbial genome database (>5700 genomes) and designed a metagenomics workflow with filtering steps to reduce DNA sequences originating from: (i) human hosts, (ii) ambiguousness/contaminants in public microbial reference genomes and (iii) the environment. Our metagenomic read classification revealed in nearly all cases the same microorganism that was determined in cultivation- and mass spectrometry-based analyses. For some patients, we identified the sequence type of the microorganism and antibiotic resistance genes through analyses of whole genome sequence (WGS) assemblies of isolates and metagenomic assemblies. Together, we conclude that genomics-based analyses of human ocular body fluid specimens can provide actionable information relevant to infectious disease management

The Extended Dawid-Skene Model:Fusing Information from Multiple Data Schemas

While label fusion from multiple noisy annotations is a well understood concept in data wrangling (tackled for example by the Dawid-Skene (DS) model), we consider the extended problem of carrying out learning when the labels themselves are not consistently annotated with the same schema. We show that even if annotators use disparate, albeit related, label-sets, we can still draw inferences for the underlying full label-set. We propose the Inter-Schema AdapteR (ISAR) to translate the fully-specified label-set to the one used by each annotator, enabling learning under such heterogeneous schemas, without the need to re-annotate the data. We apply our method to a mouse behavioural dataset, achieving significant gains (compared with DS) in out-of-sample log-likelihood (-3.40 to -2.39) and F1-score (0.785 to 0.864).Comment: Updated with Author-Preprint version following Publication in P. Cellier and K. Driessens (Eds.): ECML PKDD 2019 Workshops, CCIS 1167, pp. 121 - 136, 202

The Influence of Brightness on Functional Assessment by mfERG: A Study on Scaffolds Used in Retinal Cell Transplantation in Pigs

To determine the effect of membrane brightness on multifocal electroretinograms (mfERGs), we implanted poly lactic-co-glycolic acid (PLGA) membranes in the subretinal space of 11 porcine eyes. We compared membranes with their native shiny white color with membranes that were stained with a blue dye (Brilliant Blue). Histological and electrophysiological evaluation of the overlying retina was carried out 6 weeks after implantation. Histologically, both white and blue membranes degraded in a spongiform manner leaving a disrupted outer retina with no preserved photoreceptor segments. Multifocal ERG revealed the white membranes to have a significantly higher P1-amplitude ratio than the blue (P = 0.027), and a correlation between brightness ratio and P1-amplitude ratio was found (r = 0.762). Based on our findings, we conclude that bright subretinal objects can produce normal mfERG amplitude ratios even when the adjacent photoreceptors are missing. Functional assessment with mfERG in scaffold implant studies should therefore be evaluated with care