统计学每日论文速递[12.12]

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stat 方向,今日共计60篇

【1】 More for less: Predicting and maximizing genetic variant discovery via Bayesian nonparametrics
标题:事半功倍:通过贝叶斯非参数预测和最大化遗传变异发现
作者: Lorenzo Masoero, Tamara Broderick
链接:arxiv.org/abs/1912.0551

【2】 The Wasserstein-Fourier Distance for Stationary Time Series
标题:平稳时间序列的Wasserstein-Fourier距离
作者: Elsa Cazelles, Felipe Tobar
链接:arxiv.org/abs/1912.0550

【3】 Nonparametric Universal Copula Modeling
标题:非参数通用Copula建模
作者: Subhadeep Mukhopadhyay, Emanuel Parzen
链接:arxiv.org/abs/1912.0550

【4】 Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data
标题:混合多视图数据的集成广义凸聚类优化和特征选择
作者: Minjie Wang, Genevera I. Allen
链接:arxiv.org/abs/1912.0544

【5】 Analysis of the rate of convergence of neural network regression estimates which are easy to implement
标题:易于实现的神经网络回归估计的收敛速度分析
作者: Alina Braun, Adam Krzyzak
备注:arXiv admin note: text overlap with arXiv:1912.03921
链接:arxiv.org/abs/1912.0543

【6】 Sample Size Estimation using a Latent Variable Model for Mixed Outcome Co-Primary, Multiple Primary and Composite Endpoints
标题:使用潜变量模型估计混合结果共初级、多初级和复合端点的样本量
作者: Martina McMenamin, James M.S. Wason
链接:arxiv.org/abs/1912.0525

【7】 Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing
标题:贝叶斯混合模型的抽样:多项式时间混合的MCMC
作者: Wenlong Mou, Michael I. Jordan
链接:arxiv.org/abs/1912.0515

【8】 Robust joint modelling of longitudinal and survival data with a time-varying degrees-of-freedom parameter
标题:具有时变自由度参数的纵向数据和生存数据的鲁棒联合建模
作者: Lisa McFetridge, Jonas Wallin
链接:arxiv.org/abs/1912.0513

【9】 Measuring Spatial Allocative Efficiency in Basketball
标题:篮球运动空间配置效率的测量
作者: Nathan Sandholtz, Luke Bornn
链接:arxiv.org/abs/1912.0512

【10】 A Closer Look at Disentangling in $β$-VAE
标题:更仔细地查看$β$-vae中的解缠
作者: Harshvardhan Sikka, Cengiz Pehlevan
链接:arxiv.org/abs/1912.0512

【11】 Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse and Fragmented Functional Data
标题:用于噪声、稀疏和分段功能数据的同时配准和估计的贝叶斯框架
作者: James Matuk, Sebastian Kurtek
链接:arxiv.org/abs/1912.0512

【12】 Bayesian Copula Density Deconvolution for Zero-Inflated Data in Nutritional Epidemiology
标题:营养流行病学中零膨胀数据的贝叶斯Copula密度反卷积
作者: Abhra Sarkar, Raymond J. Carroll
链接:arxiv.org/abs/1912.0508

【13】 Fenton-Wilkinson Order Statistics and German Tanks: A Case Study of an Orienteering Relay Race
标题:Fenton-Wilkinson顺序统计量与德国坦克:一场定向接力赛的案例研究
作者: Joonas Pääkkönen
链接:arxiv.org/abs/1912.0503

【14】 Representational Rényi heterogeneity
标题:代表性Rényi异质性
作者: Abraham Nunes, Thomas Trappenberg
链接:arxiv.org/abs/1912.0503

【15】 European banks' business models and their credit risk: A cluster analysis in a high-dimensional context
标题:欧洲银行的商业模式及其信用风险:高维背景下的聚类分析
作者: Matteo Farnè, Angelos T. Vouldis
链接:arxiv.org/abs/1912.0502

【16】 Frequentist Consistency of Generalized Variational Inference
标题:广义变分推理的频率一致性
作者: Jeremias Knoblauch
链接:arxiv.org/abs/1912.0494

【17】 Center-outward quantiles and the measurement of multivariate risk
标题:中心向外分位数与多元风险的度量
作者: Jan Beirlant, Marc Hallin
链接:arxiv.org/abs/1912.0492

【18】 Asymptotic based bootstrap approach for matched pairs with missingness in a single-arm
标题:基于渐近的单臂缺失配对的Bootstrap方法
作者: Lubna Amro, Burim Ramosaj
链接:arxiv.org/abs/1912.0490

【19】 SMiRL: Surprise Minimizing RL in Dynamic Environments
标题:Smirl:动态环境中使RL最小化的惊喜
作者: Glen Berseth, Sergey Levine
链接:arxiv.org/abs/1912.0551

【20】 $Σ$-net: Ensembled Iterative Deep Neural Networks for Accelerated Parallel MR Image Reconstruction
标题:$Σ$-NET:用于加速并行MR图像重建的集成迭代深度神经网络
作者: Jo Schlemper, Kerstin Hammernik
链接:arxiv.org/abs/1912.0548

【21】 Mean-Field Neural ODEs via Relaxed Optimal Control
标题:基于松弛最优控制的平均场神经常微分方程
作者: Jean-François Jabir, Łukasz Szpruch
链接:arxiv.org/abs/1912.0547

【22】 Quantitative Universality for the Largest Eigenvalue of Sample Covariance Matrices
标题:样本协方差矩阵最大特征值的定量普适性
作者: Haoyu Wang
链接:arxiv.org/abs/1912.0547

【23】 Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data
标题:深度相关规则化:成像质谱数据的可解释和稳健的肿瘤分型
作者: Christian Etmann, Peter Maass
链接:arxiv.org/abs/1912.0545

【24】 Unsupervised Feature Selection based on Adaptive Similarity Learning and Subspace Clustering
标题:基于自适应相似学习和子空间聚类的无监督特征选择
作者: Mohsen Ghassemi Parsa, Mehdi Ghatee
链接:arxiv.org/abs/1912.0545

【25】 Self-Driving Car Steering Angle Prediction Based on Image Recognition
标题:基于图像识别的自动驾驶汽车转向角预测
作者: Shuyang Du, Andrew Simpson
备注:9 pages 13 figures. Paper originally from CS231n (Stanford) 2017
链接:arxiv.org/abs/1912.0544

【26】 Just Add Functions: A Neural-Symbolic Language Model
标题:Just Add Functions:一种神经符号语言模型
作者: David Demeter, Doug Downey
备注:Preprint of paper accepted for AAAI-2020
链接:arxiv.org/abs/1912.0542

【27】 Detecting and Correcting Adversarial Images Using Image Processing Operations and Convolutional Neural Networks
标题:利用图像处理运算和卷积神经网络检测和校正对抗性图像
作者: Huy H. Nguyen, Isao Echizen
链接:arxiv.org/abs/1912.0539

【28】 Unsupervised Transfer Learning via BERT Neuron Selection
标题:基于Bert神经元选择的无监督迁移学习
作者: Mehrdad Valipour, Carolina Bessega
链接:arxiv.org/abs/1912.0530

【29】 Integer Partitions Probability Distributions
标题:整数划分概率分布
作者: Andrew V. Sills
链接:arxiv.org/abs/1912.0530

【30】 Traffic map prediction using UNet based deep convolutional neural network
标题:基于UNET的深卷积神经网络交通地图预测
作者: Sungbin Choi
备注:NeuralIPS 2019 Traffic4cast Workshop
链接:arxiv.org/abs/1912.0528

【31】 Identifying Mislabeled Instances in Classification Datasets
标题:识别分类数据集中标注错误的实例
作者: Nicolas Michael Müller, Karla Markert
链接:arxiv.org/abs/1912.0528

【32】 BERT has a Moral Compass: Improvements of ethical and moral values of machines
标题:伯特有一个道德罗盘:机器伦理道德价值的提高
作者: Patrick Schramowski, Kristian Kersting
链接:arxiv.org/abs/1912.0523

【33】 Recurrent Transform Learning
标题:递归变换学习
作者: Megha Gupta, Angshul Majumdar
链接:arxiv.org/abs/1912.0519

【34】 Variational Learning with Disentanglement-PyTorch
标题:解缠的变分学习-PyTorch
作者: Amir H. Abdi, Sidney Fels
备注:Disentanglement Challenge - 33rd Conference on Neural Information Processing Systems (NeurIPS) - NeurIPS 2019
链接:arxiv.org/abs/1912.0518

【35】 Tensor Completion via Gaussian Process Based Initialization
标题:通过基于高斯过程的初始化来完成张量
作者: Yermek Kapushev, Evgeny Burnaev
链接:arxiv.org/abs/1912.0517

【36】 Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey
标题:带噪声标签的深度学习图像分类研究综述
作者: Görkem Algan, Ilkay Ulusoy
链接:arxiv.org/abs/1912.0517

【37】 Graph-based Multi-view Binary Learning for Image Clustering
标题:基于图的多视图二值学习图像聚类
作者: Guangqi Jiang, Xianping Fu
链接:arxiv.org/abs/1912.0515

【38】 Is Feature Diversity Necessary in Neural Network Initialization?
标题:神经网络初始化是否需要特征多样性?
作者: Yaniv Blumenfeld, Daniel Soudry
链接:arxiv.org/abs/1912.0513

【39】 Marginalized State Distribution Entropy Regularization in Policy Optimization
标题:政策优化中的边缘状态分布熵正则化
作者: Riashat Islam, Doina Precup
备注:In Submission; Appeared at NeurIPS 2019 Deep Reinforcement Learning Workshop
链接:arxiv.org/abs/1912.0512

【40】 Towards Better Forecasting by Fusing Near and Distant Future Visions
标题:通过融合近期和遥远的未来愿景实现更好的预测
作者: Jiezhu Cheng, Zibin Zheng
备注:Accepted by AAAI 2020
链接:arxiv.org/abs/1912.0512

【41】 Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning
标题:强化学习的双重鲁棒Off-Policy Actor-Critic算法
作者: Riashat Islam, Doina Precup
备注:In Submission; Appeared at NeurIPS 2019 Workshop on Safety and Robustness in Decision Making
链接:arxiv.org/abs/1912.0510

【42】 Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods
标题:策略梯度方法中贴现未来状态分布的熵正则化
作者: Riashat Islam, Doina Precup
备注:In Submission; Appeared at NeurIPS 2019 Optimization Foundations of Reinforcement Learning Workshop
链接:arxiv.org/abs/1912.0510

【43】 Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches
标题:可解释性事实表:可解释方法的系统评估框架
作者: Kacper Sokol, Peter Flach
备注:Conference on Fairness, Accountability, and Transparency (FAT* '20), January 27-30, 2020, Barcelona, Spain
链接:arxiv.org/abs/1912.0510

【44】 On Neural Learnability of Chaotic Dynamics
标题:关于混沌动力学的神经可学习性
作者: Ziwei Li, Sai Ravela
链接:arxiv.org/abs/1912.0508

【45】 An Improving Framework of regularization for Network Compression
标题:一种改进的网络压缩正则化框架
作者: E Zhenqian, Gao Weiguo
链接:arxiv.org/abs/1912.0507

【46】 Multimodal Generative Models for Compositional Representation Learning
标题:成分表征学习的多模态生成模型
作者: Mike Wu, Noah Goodman
链接:arxiv.org/abs/1912.0507

【47】 Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds
标题:基于情感分析和群体智慧的微博事件结果预测
作者: Rahul Radhakrishnan Iyer, Katia Sycara
链接:arxiv.org/abs/1912.0506

【48】 Efficient crowdsourcing of crowd-generated microtasks
标题:群体生成的微任务的有效众包
作者: Abigail Hotaling, James P. Bagrow
备注:19 pages, 5 figures
链接:arxiv.org/abs/1912.0504

【49】 Imitation Learning via Off-Policy Distribution Matching
标题:基于非策略分布匹配的模仿学习
作者: Ilya Kostrikov, Jonathan Tompson
链接:arxiv.org/abs/1912.0503

【50】 Continual egocentric object recognition
标题:连续自我中心对象识别
作者: Luca Erculiani, Andrea Passerini
链接:arxiv.org/abs/1912.0502

【51】 Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data
标题:在低分辨率卫星时间序列数据中检测几乎看不见的道路
作者: Stefan Oehmcke, Fabian Gieseke
链接:arxiv.org/abs/1912.0502

【52】 Design and Interpretation of Universal Adversarial Patches in Face Detection
标题:人脸检测中通用对抗性斑块的设计与解释
作者: Xiao Yang, Jun Zhu
链接:arxiv.org/abs/1912.0502

【53】 Oktoberfest Food Dataset
标题:Oktoberfest食品数据集
作者: Alexander Ziller, Stephan Günnemann
链接:arxiv.org/abs/1912.0500

【54】 Almost Uniform Sampling From Neural Networks
标题:神经网络的几乎均匀采样
作者: Changlong Wu, Narayana Prasad Santhanam
链接:arxiv.org/abs/1912.0499

【55】 Phase Retrieval using Conditional Generative Adversarial Networks
标题:基于条件生成对抗网络的相位检索
作者: Tobias Uelwer, Stefan Harmeling
链接:arxiv.org/abs/1912.0498

【56】 Advances and Open Problems in Federated Learning
标题:联邦学习的进展和存在的问题
作者: Peter Kairouz, et al. (9 additional authors not shown)
链接:arxiv.org/abs/1912.0497

【57】 A Two-Stage Approach to Few-Shot Learning for Image Recognition
标题:一种用于图像识别的两阶段少炮学习方法
作者: Debasmit Das, C. S. George Lee
链接:arxiv.org/abs/1912.0497

【58】 Neural Memory Networks for Robust Classification of Seizure Type
标题:神经记忆网络用于癫痫类型的鲁棒分类
作者: David Ahmedt-Aristizabal, Clinton Fookes
链接:arxiv.org/abs/1912.0496

【59】 Medication Regimen Extraction From Clinical Conversations
标题:从临床对话中提取用药方案
作者: Sai P. Selvaraj, Sandeep Konam
备注:To appear in Proceedings of International Workshop on Health Intelligence (W3PHIAI) of the 34th AAAI Conference on Artificial Intelligence, 2020
链接:arxiv.org/abs/1912.0496

【60】 Analyzing and Improving the Image Quality of StyleGAN
标题:StyleGAN图像质量分析与改进
作者: Tero Karras, Timo Aila
链接:arxiv.org/abs/1912.0495

机器翻译,仅供参考

发布于 2019-12-12 10:59