图 书 馆开课单位--德克萨斯大学
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11Practical RL: Representation, interaction, synthesis, and morality (PRISM)[实践RL：表现、互动、综合与道德（PRISM）]
Peter Stone(德克萨斯大学) When scaling up Reinforcement Learning (RL) to large continuous domains with imperfect representations and hierarchical structure, we often try applyi...
热度：39
Peter Stone(德克萨斯大学) When scaling up Reinforcement Learning (RL) to large continuous domains with imperfect representations and hierarchical structure, we often try applyi...
热度：39
12Robust PCA and Collaborative Filtering: Rejecting Outliers, Identifying Manipulators[鲁棒PCA与协同过滤：剔除异常值，识别机械手]
Constantine Caramanis(德克萨斯大学) Principal Component Analysis is one of the most widely used techniques for dimensionality reduction. Nevertheless, it is plagued by sensitivity to out...
热度：35
Constantine Caramanis(德克萨斯大学) Principal Component Analysis is one of the most widely used techniques for dimensionality reduction. Nevertheless, it is plagued by sensitivity to out...
热度：35
13Active learning of neural response functions with Gaussian processes[高斯过程神经响应函数的主动学习]
Mijung Park(德克萨斯大学) A sizable literature has focused on the problem of estimating a low-dimensional feature space capturing a neuron's stimulus sensitivity. However, ...
热度：26
Mijung Park(德克萨斯大学) A sizable literature has focused on the problem of estimating a low-dimensional feature space capturing a neuron's stimulus sensitivity. However, ...
热度：26
14Graphical Models via Generalized Linear Models[基于广义线性模型的图形模型]
Eunho Yang(德克萨斯大学) Undirected graphical models, or Markov networks, such as Gaussian graphical models and Ising models enjoy popularity in a variety of applications. In ...
热度：51
Eunho Yang(德克萨斯大学) Undirected graphical models, or Markov networks, such as Gaussian graphical models and Ising models enjoy popularity in a variety of applications. In ...
热度：51
15Focusing Human Attention on the "Right" Visual Data[把人类的注意力集中在“正确”的视觉数据上]
Kristen Grauman(德克萨斯大学) Widespread visual sensors and unprecedented connectivity have left us awash with visual data‐‐‐from online photo collections, home videos, news foo...
热度：32
Kristen Grauman(德克萨斯大学) Widespread visual sensors and unprecedented connectivity have left us awash with visual data‐‐‐from online photo collections, home videos, news foo...
热度：32
16Words as reflections of psychological state[语言作为心理状态的反映]
James W. Pennebaker(德克萨斯大学) Pennebaker’s research explores the links between traumatic experiences, expressive writing, natural language use, and physical and mental health...
热度：43
James W. Pennebaker(德克萨斯大学) Pennebaker’s research explores the links between traumatic experiences, expressive writing, natural language use, and physical and mental health...
热度：43
17Grounded Language Learning[扎根语言学习]
Raymond J. Mooney(德克萨斯大学) Most approaches to semantics in computational linguistics represent meaning in terms of words or abstract symbols. Grounded-language research bases th...
热度：119
Raymond J. Mooney(德克萨斯大学) Most approaches to semantics in computational linguistics represent meaning in terms of words or abstract symbols. Grounded-language research bases th...
热度：119
18Multi-Subspace Representation and Discovery[多子空间表示和发现]
Chris Ding(德克萨斯大学) This paper presents the multi-subspace discovery problem and provides a theoretical solution which is guaranteed to recover the number of subspaces, t...
热度：71
Chris Ding(德克萨斯大学) This paper presents the multi-subspace discovery problem and provides a theoretical solution which is guaranteed to recover the number of subspaces, t...
热度：71
19Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams[将新颖的类检测与概念漂移数据流的分类相结合]
Latifur Khan(德克萨斯大学) In a typical data stream classification task, it is assumed that the total number of classes are fixed. This assumption may not be valid in a real str...
热度：62
Latifur Khan(德克萨斯大学) In a typical data stream classification task, it is assumed that the total number of classes are fixed. This assumption may not be valid in a real str...
热度：62
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