Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science

As the field of data science continues to grow, there will be an ever-increasing demand for tools that make machine learning accessible to non-experts. In this paper, we introduce the concept of tree-based pipeline optimization for automating one of the most tedious parts of machine learning---pipeline design. We implement an open source Tree-based Pipeline Optimization Tool (TPOT) in Python and demonstrate its effectiveness on a series of simulated and real-world benchmark data sets. In particular, we show that TPOT can design machine learning pipelines that provide a significant improvement over a basic machine learning analysis while requiring little to no input nor prior knowledge from the user. We also address the tendency for TPOT to design overly complex pipelines by integrating Pareto optimization, which produces compact pipelines without sacrificing classification accuracy. As such, this work represents an important step toward fully automating machine learning pipeline design.Comment: 8 pages, 5 figures, preprint to appear in GECCO 2016, edits not yet made from reviewer comment

Recurrently Predicting Hypergraphs

This work considers predicting the relational structure of a hypergraph for a given set of vertices, as common for applications in particle physics, biological systems and other complex combinatorial problems. A problem arises from the number of possible multi-way relationships, or hyperedges, scaling in $\mathcal{O}(2^n)$ for a set of $n$ elements. Simply storing an indicator tensor for all relationships is already intractable for moderately sized $n$, prompting previous approaches to restrict the number of vertices a hyperedge connects. Instead, we propose a recurrent hypergraph neural network that predicts the incidence matrix by iteratively refining an initial guess of the solution. We leverage the property that most hypergraphs of interest are sparsely connected and reduce the memory requirement to $\mathcal{O}(nk)$, where $k$ is the maximum number of positive edges, i.e., edges that actually exist. In order to counteract the linearly growing memory cost from training a lengthening sequence of refinement steps, we further propose an algorithm that applies backpropagation through time on randomly sampled subsequences. We empirically show that our method can match an increase in the intrinsic complexity without a performance decrease and demonstrate superior performance compared to state-of-the-art models

Концепция моделирования проектного управления информационными ресурсами на основе показателей финансового состояния предприятия

В статье рассматриваются две составляющие доходной части информационных ресурсов – увеличение оборачиваемости оборотных средств предприятия за счет сокращения времени на принятие решения и сокращения резервных фондов за счет снижения уровня неопределенности

A phase II study of paclitaxel in heavily pretreated patients with small-cell lung cancer.

The purpose of the study was to delineate the efficacy and toxicity of paclitaxel (Taxol, Bristol Myers Squibb) in the treatment of drug resistant small-cell lung cancer (SCLC). Patients with SCLC relapsing within 3 months of cytotoxic therapy received paclitaxel 175 mg m(-2) intravenously over 3 h every 3 weeks. The dose of paclitaxel was adjusted to the toxicity encountered in the previous cycle. Of 24 patients entered into the study, 24 and 21 were assessable for response and toxicity respectively. There were two early deaths and two toxic deaths. No complete and seven partial responses (29%) (95%CI 12-51%) were observed and five patients had disease stabilization. The median survival (n = 21) was 100 days. Life-threatening toxicity occurred in four patients; in others (non)-haematological toxicity was manageable. Paclitaxel is active in drug-resistant SCLC. Further investigation in combination with other active agents in this poor prognosis group is appropriate

Rigorous mean-field dynamics of lattice bosons: Quenches from the Mott insulator

We provide a rigorous derivation of Gutzwiller mean-field dynamics for lattice bosons, showing that it is exact on fully connected lattices. We apply this formalism to quenches in the interaction parameter from the Mott insulator to the superfluid state. Although within mean-field the Mott insulator is a steady state, we show that a dynamical critical interaction $U_d$ exists, such that for final interaction parameter $U_f>U_d$ the Mott insulator is exponentially unstable towards emerging long-range superfluid order, whereas for $U_f<U_d$ the Mott insulating state is stable. We discuss the implications of this prediction for finite-dimensional systems.Comment: 6 pages, 3 figures, published versio

Large-Scale Sleep Condition Analysis Using Selfies from Social Media

Sleep condition is closely related to an individual's health. Poor sleep conditions such as sleep disorder and sleep deprivation affect one's daily performance, and may also cause many chronic diseases. Many efforts have been devoted to monitoring people's sleep conditions. However, traditional methodologies require sophisticated equipment and consume a significant amount of time. In this paper, we attempt to develop a novel way to predict individual's sleep condition via scrutinizing facial cues as doctors would. Rather than measuring the sleep condition directly, we measure the sleep-deprived fatigue which indirectly reflects the sleep condition. Our method can predict a sleep-deprived fatigue rate based on a selfie provided by a subject. This rate is used to indicate the sleep condition. To gain deeper insights of human sleep conditions, we collected around 100,000 faces from selfies posted on Twitter and Instagram, and identified their age, gender, and race using automatic algorithms. Next, we investigated the sleep condition distributions with respect to age, gender, and race. Our study suggests among the age groups, fatigue percentage of the 0-20 youth and adolescent group is the highest, implying that poor sleep condition is more prevalent in this age group. For gender, the fatigue percentage of females is higher than that of males, implying that more females are suffering from sleep issues than males. Among ethnic groups, the fatigue percentage in Caucasian is the highest followed by Asian and African American.Comment: 2017 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS'17

Self-Guided Diffusion Models

Diffusion models have demonstrated remarkable progress in image generation quality, especially when guidance is used to control the generative process. However, guidance requires a large amount of image-annotation pairs for training and is thus dependent on their availability, correctness and unbiasedness. In this paper, we eliminate the need for such annotation by instead leveraging the flexibility of self-supervision signals to design a framework for self-guided diffusion models. By leveraging a feature extraction function and a self-annotation function, our method provides guidance signals at various image granularities: from the level of holistic images to object boxes and even segmentation masks. Our experiments on single-label and multi-label image datasets demonstrate that self-labeled guidance always outperforms diffusion models without guidance and may even surpass guidance based on ground-truth labels, especially on unbalanced data. When equipped with self-supervised box or mask proposals, our method further generates visually diverse yet semantically consistent images, without the need for any class, box, or segment label annotation. Self-guided diffusion is simple, flexible and expected to profit from deployment at scale