图 书 馆开课单位--马克斯普朗克研究所
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91Weighted Substructure Mining for Image Analysis[图像分析的加权子结构挖掘]
Sebastian Nowozin(马克斯普朗克研究所) In web-related applications of image categorization, it is desirable to derive an interpretable classification rule with high accuracy. Using the ...
热度：14
Sebastian Nowozin(马克斯普朗克研究所) In web-related applications of image categorization, it is desirable to derive an interpretable classification rule with high accuracy. Using the ...
热度：14
92Psychoacoustic Influences on the Neural Correlates of music Syntactic Processing[心理声学对音乐句法加工神经相关性的影响]
Sebastian Jentschke(马克斯普朗克研究所) Music consists of perceptually discrete elements that are organized according to syntactic regularities. Violations of these regularities typically el...
热度：55
Sebastian Jentschke(马克斯普朗克研究所) Music consists of perceptually discrete elements that are organized according to syntactic regularities. Violations of these regularities typically el...
热度：55
93Semantic Knowledge Bases from Web Sources[基于Web源的语义知识库]
Hady W. Lauw, Fabian M. Suchanek, Ralf Schenkel, Martin Theobald, Gerhard Weikum(马克斯普朗克研究所) The advent of knowledge-sharing communities such as Wikipedia and the progress in scalable information extraction from Web sources has enabled the aut...
热度：26
Hady W. Lauw, Fabian M. Suchanek, Ralf Schenkel, Martin Theobald, Gerhard Weikum(马克斯普朗克研究所) The advent of knowledge-sharing communities such as Wikipedia and the progress in scalable information extraction from Web sources has enabled the aut...
热度：26
94Measuring User Influence on Twitter: The Million Follower Fallacy[衡量用户对Twitter的影响：百万追随者谬论]
Meeyoung Cha(马克斯普朗克研究所) Directed links in social media could represent anything from intimate friendships to common interests, or even a passion for breaking news or celebrit...
热度：36
Meeyoung Cha(马克斯普朗克研究所) Directed links in social media could represent anything from intimate friendships to common interests, or even a passion for breaking news or celebrit...
热度：36
95A note of caution regarding distances on graphs[关于图上距离的注意事项]
Ulrike von Luxburg(马克斯普朗克研究所) Non-geometric data is often represented in form of a graph where edges represent similarity or local relationships between instances. One elegant way ...
热度：26
Ulrike von Luxburg(马克斯普朗克研究所) Non-geometric data is often represented in form of a graph where edges represent similarity or local relationships between instances. One elegant way ...
热度：26
96Solution Stability in Linear Programming Relaxations: Graph Partitioning and Unsupervised Learning[线性规划松弛的解稳定性：图分割和无监督学习]
Sebastian Nowozin(马克斯普朗克研究所) We propose a new method to quantify the solution stability of a large class of combinatorial optimization problems arising in machine learning. As pra...
热度：83
Sebastian Nowozin(马克斯普朗克研究所) We propose a new method to quantify the solution stability of a large class of combinatorial optimization problems arising in machine learning. As pra...
热度：83
97Convex Variational Bayesian Inference for Large Scale Generalized Linear Models[大尺度广义线性模型的凸变分贝叶斯推理]
Hannes Nickisch(马克斯普朗克研究所) We show how variational Bayesian inference can be implemented for very large generalized linear models. Our relaxation is proven to be a convex proble...
热度：21
Hannes Nickisch(马克斯普朗克研究所) We show how variational Bayesian inference can be implemented for very large generalized linear models. Our relaxation is proven to be a convex proble...
热度：21
98Sparse Multiscale Gaussian Process Regression[稀疏多尺度高斯过程回归]
Christian Walder(马克斯普朗克研究所) Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are ...
热度：192
Christian Walder(马克斯普朗克研究所) Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are ...
热度：192
99Gaussian Process Product Models for Nonparametric Nonstationarity[非参数非平稳性的高斯过程产品模型]
Oliver Stegle(马克斯普朗克研究所) Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covarian...
热度：69
Oliver Stegle(马克斯普朗克研究所) Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covarian...
热度：69
100A Decoupled Approach to Exemplar-based Unsupervised Learning[基于范例的无监督学习的解耦方法]
Sebastian Nowozin(马克斯普朗克研究所) A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by...
热度：51
Sebastian Nowozin(马克斯普朗克研究所) A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by...
热度：51