图 书 馆开课单位--加州大学圣地亚哥分校
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11Information Geometry[信息几何]
Sanjoy Dasgupta(加州大学圣地亚哥分校) This tutorial will focus on entropy, exponential families, and information projection. We'll start by seeing the sense in which entropy is the onl...
热度：263
Sanjoy Dasgupta(加州大学圣地亚哥分校) This tutorial will focus on entropy, exponential families, and information projection. We'll start by seeing the sense in which entropy is the onl...
热度：263
12Log-linear Models and Conditional Random Fields[对数线性模型和条件随机领域]
Charles Elkan(加州大学圣地亚哥分校) Log-linear models are a far-reaching extension of logistic regression, while con- ditional random fields (CRFs) are a special case of log-linear model...
热度：59
Charles Elkan(加州大学圣地亚哥分校) Log-linear models are a far-reaching extension of logistic regression, while con- ditional random fields (CRFs) are a special case of log-linear model...
热度：59
13Lunch debate 23.5.2005[午餐辩论2005.5.23]
David McAllester;Zoubin Ghahramani; John Langford;Yann LeCun;Partha Niyogi;Sanjoy Dasgupta;Yasemin Altun(加州大学圣地亚哥分校)
热度：26
David McAllester;Zoubin Ghahramani; John Langford;Yann LeCun;Partha Niyogi;Sanjoy Dasgupta;Yasemin Altun(加州大学圣地亚哥分校)
热度：26
14Randomized partition trees for exact nearest neighbor search[精确的最近邻搜索的随机分配树]
Sanjoy Dasgupta(加州大学圣地亚哥分校) The k-d tree was one of the first spatial data structures proposed for nearest neighbor search. Its efficacy is diminished in high-dimensional spaces,...
热度：19
Sanjoy Dasgupta(加州大学圣地亚哥分校) The k-d tree was one of the first spatial data structures proposed for nearest neighbor search. Its efficacy is diminished in high-dimensional spaces,...
热度：19
15Learning Dictionaries of Stable Autoregressive Models for Audio Scene Analysis[用于音频场景分析的稳定自回归模型的学习字典]
Youngmin Cho(加州大学圣地亚哥分校) In this paper, we explore an application of basis pursuit to audio scene analysis. The goal of our work is to detect when certain sounds are present ...
热度：46
Youngmin Cho(加州大学圣地亚哥分校) In this paper, we explore an application of basis pursuit to audio scene analysis. The goal of our work is to detect when certain sounds are present ...
热度：46
16Log-linear Models and Conditional Random Fields[对数线性模型和条件随机场]
Charles Elkan(加州大学圣地亚哥分校) Log-linear models are a far-reaching extension of logistic regression, while con- ditional random fields (CRFs) are a special case of log-linear model...
热度：23
Charles Elkan(加州大学圣地亚哥分校) Log-linear models are a far-reaching extension of logistic regression, while con- ditional random fields (CRFs) are a special case of log-linear model...
热度：23
17Augmented Information Assimilation: Social and Algorithmic Web Aids for the Information Long Tail[增强信息同化：信息长尾算法Web和社交的辅助]
Brynn M. Evans(加州大学圣地亚哥分校) This study examines how users integrate new World Wide Webservices, such as social bookmarking, with everyday information assimilation practices.
热度：24
Brynn M. Evans(加州大学圣地亚哥分校) This study examines how users integrate new World Wide Webservices, such as social bookmarking, with everyday information assimilation practices.
热度：24
18Sketching and Streaming for Distributions[分发的草绘和流式传输]
Andrew McGregor(加州大学圣地亚哥分校) In this talk we look at the problem of sketching distributions in the data-stream model. This is a model that has become increasingly popular over the...
热度：30
Andrew McGregor(加州大学圣地亚哥分校) In this talk we look at the problem of sketching distributions in the data-stream model. This is a model that has become increasingly popular over the...
热度：30
19Steppest descent analysis for unregularized linear prediction with strictly convex penalties
Matus Telgarsky(加州大学圣地亚哥分校) This manuscript presents a convergence analysis, generalized from a study of boosting, of unregularized linear prediction. Here the empirical risk &md...
热度：35
Matus Telgarsky(加州大学圣地亚哥分校) This manuscript presents a convergence analysis, generalized from a study of boosting, of unregularized linear prediction. Here the empirical risk &md...
热度：35
20Finding a Better k: A Psychophysical Investigation of Clustering[寻找一个更好的k：聚类的心理物理研究]
Joshua M. Lewis(加州大学圣地亚哥分校) Finding the number of groups in a data set, k, is an important problem in the field of unsupervised machine learning with applications across many sci...
热度：51
Joshua M. Lewis(加州大学圣地亚哥分校) Finding the number of groups in a data set, k, is an important problem in the field of unsupervised machine learning with applications across many sci...
热度：51