Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data

We present a Bayesian non-negative tensor factorization model for count-valued tensor data, and develop scalable inference algorithms (both batch and online) for dealing with massive tensors. Our generative model can handle overdispersed counts as well as infer the rank of the decomposition. Moreover, leveraging a reparameterization of the Poisson distribution as a multinomial facilitates conjugacy in the model and enables simple and efficient Gibbs sampling and variational Bayes (VB) inference updates, with a computational cost that only depends on the number of nonzeros in the tensor. The model also provides a nice interpretability for the factors; in our model, each factor corresponds to a "topic". We develop a set of online inference algorithms that allow further scaling up the model to massive tensors, for which batch inference methods may be infeasible. We apply our framework on diverse real-world applications, such as \emph{multiway} topic modeling on a scientific publications database, analyzing a political science data set, and analyzing a massive household transactions data set.Comment: ECML PKDD 201

Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span

BACKGROUND: The statistical modeling of biomedical corpora could yield integrated, coarse-to-fine views of biological phenomena that complement discoveries made from analysis of molecular sequence and profiling data. Here, the potential of such modeling is demonstrated by examining the 5,225 free-text items in the Caenorhabditis Genetic Center (CGC) Bibliography using techniques from statistical information retrieval. Items in the CGC biomedical text corpus were modeled using the Latent Dirichlet Allocation (LDA) model. LDA is a hierarchical Bayesian model which represents a document as a random mixture over latent topics; each topic is characterized by a distribution over words. RESULTS: An LDA model estimated from CGC items had better predictive performance than two standard models (unigram and mixture of unigrams) trained using the same data. To illustrate the practical utility of LDA models of biomedical corpora, a trained CGC LDA model was used for a retrospective study of nematode genes known to be associated with life span modification. Corpus-, document-, and word-level LDA parameters were combined with terms from the Gene Ontology to enhance the explanatory value of the CGC LDA model, and to suggest additional candidates for age-related genes. A novel, pairwise document similarity measure based on the posterior distribution on the topic simplex was formulated and used to search the CGC database for "homologs" of a "query" document discussing the life span-modifying clk-2 gene. Inspection of these document homologs enabled and facilitated the production of hypotheses about the function and role of clk-2. CONCLUSION: Like other graphical models for genetic, genomic and other types of biological data, LDA provides a method for extracting unanticipated insights and generating predictions amenable to subsequent experimental validation

Adolescent D-amphetamine treatment in a rodent model of ADHD: pro-cognitive effects during adolescence and cocaine abuse risk during adulthood

Attention-deficit/hyperactivity disorder (ADHD) is comorbid with cocaine abuse. Whereas initiating ADHD medication in childhood does not alter later cocaine abuse risk, initiating medication during adolescence may increase risk. Preclinical work in the Spontaneously Hypertensive Rat (SHR) model of ADHD found that adolescent methylphenidate increased cocaine self-administration in adulthood, suggesting a need to identify alternatively efficacious medications for teens with ADHD. We examined effects of adolescent d-amphetamine treatment on strategy set shifting performance during adolescence and on cocaine self-administration and reinstatement of cocaine-seeking behavior (cue reactivity) during adulthood in male SHR, Wistar- Kyoto (inbred control), and Wistar (outbred control) rats. During the set shift phase, adolescent SHR needed more trials and had a longer latency to reach criterion, made more regressive errors and trial omissions, and exhibited slower and more variable lever press reaction times. d- Amphetamine improved performance only in SHR by increasing choice accuracy and decreasing errors and latency to criterion. In adulthood, SHR self-administered more cocaine, made more cocaine-seeking responses, and took longer to extinguish lever responding than control strains. Adolescent d-amphetamine did not alter cocaine self-administration in adult rats of any strain, but reduced cocaine seeking during the first of seven reinstatement test sessions in adult SHR. These findings highlight utility of SHR in modeling cognitive dysfunction and comorbid cocaine abuse in ADHD. Unlike methylphenidate, d-amphetamine improved several aspects of flexible learning in adolescent SHR and did not increase cocaine intake or cue reactivity in adult SHR. Thus, adolescent d-amphetamine was superior to methylphenidate in this ADHD model

Label-Dependencies Aware Recurrent Neural Networks

In the last few years, Recurrent Neural Networks (RNNs) have proved effective on several NLP tasks. Despite such great success, their ability to model \emph{sequence labeling} is still limited. This lead research toward solutions where RNNs are combined with models which already proved effective in this domain, such as CRFs. In this work we propose a solution far simpler but very effective: an evolution of the simple Jordan RNN, where labels are re-injected as input into the network, and converted into embeddings, in the same way as words. We compare this RNN variant to all the other RNN models, Elman and Jordan RNN, LSTM and GRU, on two well-known tasks of Spoken Language Understanding (SLU). Thanks to label embeddings and their combination at the hidden layer, the proposed variant, which uses more parameters than Elman and Jordan RNNs, but far fewer than LSTM and GRU, is more effective than other RNNs, but also outperforms sophisticated CRF models.Comment: 22 pages, 3 figures. Accepted at CICling 2017 conference. Best Verifiability, Reproducibility, and Working Description awar

A critical appraisal of gabapentinoids for pain in cancer patients.

Gabapentinoids are frequently used in the management of cancer pain. In recent Cochrane systematic reviews, although there was an abundance of evidence relating to non-cancer pain, only a few studies related to cancer pain. This review summarizes recent randomised controlled trials (RCTs) evaluating the use of gabapentinoids for tumour-related (as monotherapy or part of combination therapy) and treatment-related pain. Recent findings: for tumour-related pain, ten out of thirteen studies showed statistically significant benefits in favour of gabapentinoids. When used, as part of monotherapy or combination therapy, benefits were observed in five out of six studies evaluating gabapentin, and in six out of eight studies evaluating pregabalin. For treatment-related pain, none of the four studies (two gabapentin, two pregabalin) showed statistically significant benefits in favour of gabapentinoids. Unfortunately, many of the studies included were limited by small sample size, lack of blinding, and inadequate follow-up. Summary: more and better quality studies are required, although it may be challenging to accomplish in this patient population. Gabapentinoids may offer benefits to cancer patients with pain, but careful titration and monitoring of adverse effects is necessary

Bronchoscopic lung volume reduction with endobronchial valves for patients with heterogeneous emphysema and intact interlobar fissures (The BeLieVeR-HIFi trial): study design and rationale

Although lung volume reduction surgery improves survival in selected patients with emphysema, there has been ongoing interest in developing and evaluating bronchoscopic approaches to try to reduce lung volumes with less morbidity and mortality. The placement of endobronchial valves is one such technique, and although some patients have had a significant improvement, responses have been inconsistent because collateral ventilation prevents lobar atelectasis. We describe the protocol of a trial (ISRCTN04761234) aimed to show that a responder phenotype, patients with heterogeneous emphysema and intact interlobar fissures on CT scanning, can be identified prospectively, leading to a consistent benefit in clinical practice

Optimal client recommendation for market makers in illiquid financial products

The process of liquidity provision in financial markets can result in prolonged exposure to illiquid instruments for market makers. In this case, where a proprietary position is not desired, pro-actively targeting the right client who is likely to be interested can be an effective means to offset this position, rather than relying on commensurate interest arising through natural demand. In this paper, we consider the inference of a client profile for the purpose of corporate bond recommendation, based on typical recorded information available to the market maker. Given a historical record of corporate bond transactions and bond meta-data, we use a topic-modelling analogy to develop a probabilistic technique for compiling a curated list of client recommendations for a particular bond that needs to be traded, ranked by probability of interest. We show that a model based on Latent Dirichlet Allocation offers promising performance to deliver relevant recommendations for sales traders.Comment: 12 pages, 3 figures, 1 tabl

Arsonists or firefighters? Affectiveness in agile software development

In this paper, we present an analysis of more than 500K comments from open-source repositories of software systems developed using agile methodologies. Our aim is to empirically determine how developers interact with each other under certain psychological conditions generated by politeness, sentiment and emotion expressed within developers' comments. Developers involved in an open-source projects do not usually know each other; they mainly communicate through mailing lists, chat, and tools such as issue tracking systems. The way in which they communicate a ects the development process and the productivity of the people involved in the project. We evaluated politeness, sentiment and emotions of comments posted by agile developers and studied the communication ow to understand how they interacted in the presence of impolite and negative comments (and vice versa). Our analysis shows that \ re ghters" prevail. When in presence of impolite or negative comments, the probability of the next comment being impolite or negative is 13% and 25%, respectively; ANGER however, has a probability of 40% of being followed by a further ANGER comment. The result could help managers take control the development phases of a system, since social aspects can seriously a ect a developer's productivity. In a distributed agile environment this may have a particular resonance

Bronchoscopic lung volume reduction with endobronchial valves for patients with heterogeneous emphysema and intact interlobar fissures (the BeLieVeR-HIFi study): a randomised controlled trial

Background Lung volume reduction surgery improves survival in selected patients with emphysema, and has generated interest in bronchoscopic approaches that might achieve the same effect with less morbidity and mortality. Previous trials with endobronchial valves have yielded modest group benefits because when collateral ventilation is present it prevents lobar atelectasis. Methods We did a single-centre, double-blind sham-controlled trial in patients with both heterogeneous emphysema and a target lobe with intact interlobar fissures on CT of the thorax. We enrolled stable outpatients with chronic obstructive pulmonary disease who had a forced expiratory volume in 1 s (FEV1) of less than 50% predicted, significant hyperinflation (total lung capacity >100% and residual volume >150%), a restricted exercise capacity (6 min walking distance <450 m), and substantial breathlessness (MRC dyspnoea score ≥3). Participants were randomised (1:1) by computer-generated sequence to receive either valves placed to achieve unilateral lobar occlusion (bronchoscopic lung volume reduction) or a bronchoscopy with sham valve placement (control). Patients and researchers were masked to treatment allocation. The study was powered to detect a 15% improvement in the primary endpoint, the FEV1 3 months after the procedure. Analysis was on an intention-to-treat basis. The trial is registered at controlled-trials.com, ISRCTN04761234. Findings 50 patients (62% male, FEV1 [% predicted] mean 31·7% [SD 10·2]) were enrolled to receive valves (n=25) or sham valve placement (control, n=25) between March 1, 2012, and Sept 30, 2013. In the bronchoscopic lung volume reduction group, FEV1 increased by a median 8·77% (IQR 2·27–35·85) versus 2·88% (0–8·51) in the control group (Mann-Whitney p=0·0326). There were two deaths in the bronchoscopic lung volume reduction group and one control patient was unable to attend for follow-up assessment because of a prolonged pneumothorax. Interpretation Unilateral lobar occlusion with endobronchial valves in patients with heterogeneous emphysema and intact interlobar fissures produces significant improvements in lung function. There is a risk of significant complications and further trials are needed that compare valve placement with lung volume reduction surgery