开课单位--普林斯顿大学

41
Verification of Biochemical Activity for Protein Monolayers Nanostructured on Gold Surfaces[金属表面纳米结构蛋白质单分子层生化活性的验证]
  Giacinto Scoles(普林斯顿大学) We demonstrate that an Atomic Force Microscope (AFM) can be used to immobilize a di-cysteine-terminated protein (Maltose Binding Protein, MBP-cys-cys ...
热度：45

42
Kullback-Leibler Divergence Estimation of Continuous Distributions[连续分布的kullback-leibler散度估计]
  Fernando Perez-Cruz(普林斯顿大学 ) We present a universal method for estimating the KL divergence between continuous densities and we prove it converges almost surely. Divergence estima...
热度：34

43
Quasar classification and characterization from broadband multi-filter, multi-epoch data sets[基于宽带多滤波多历元数据集的类星体分类与表征 ]
  Jo Bovy(普林斯顿大学 ) Quasars—actively accreting supermassive black holes—are among the most luminous objects in the Universe. Large samples of quasars can be u...
热度：30

44
k-NN Regression Adapts to Local Intrinsic Dimension[k-NN回归适应于局部固有维数]
  Samory Kpotufe(普林斯顿大学) Many nonparametric regressors were recently shown to converge at rates that depend only on the intrinsic dimension of data. These regressors thus esca...
热度：72

45
What Do Unique Games, Structural Biology and the Low-Rank Matrix Completion Problem Have In Common[独特的游戏，结构生物学和低秩矩阵完成问题有什么共同之处]
  Amit Singer(普林斯顿大学) We will formulate several data-driven applications as MAX2LIN and d-to-1 games, and show how to (approximately) solve them using efficient spectral an...
热度：58

46
An Introductory Science Curriculum for 21st Century Biologists[21世纪生物学家入门科学课程]
  David Botstein(普林斯顿大学) How will biology move beyond the Human Genome Project and the task of reducing living things to their genetic sequences? According to David Botstein, ...
热度：73

47
Complexity Theoretic Lower Bounds for Sparse Principal Component Detection[稀疏主成分检测的复杂性理论下界]
  Quentin Berthet(普林斯顿大学) In the context of sparse principal component detection, we bring evidence towards the existence of a statistical price to pay for computational effici...
热度：42

48
Scalable Inference of Overlapping Communities[重叠社区的可扩展推理]
  Prem Gopalan(普林斯顿大学) We develop a scalable algorithm for posterior inference of overlapping communities in large networks. Our algorithm is based on stochastic variational...
热度：58

49
Hierarchical Maximum Entropy Density Estimation[分层最大熵密度估计]
  Miroslav Dudík(普林斯顿大学) We study the problem of simultaneously estimating several densities where the datasets are organized into overlapping groups, such as a hierarchy. For...
热度：80

50
Hierarchical Gaussian Naive Bayes Classifier for Multiple-Subject fMRI Data[多学科fMRI数据的分层高斯朴素贝叶斯分类器]
  Indrayana Rustandi(普林斯顿大学) The Gaussian Na¨ıve Bayes (GNB) [2] classifier has been successfully applied to fMRI data. However, it is not specifically designed to account fo...
热度：78