图 书 馆开课单位--德克萨斯大学
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1Information Theoretic Regularization for Semi-Supervised Boosting [半监督提升的信息论正则化]
Lei Zheng(德克萨斯大学) We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradi...
热度：68
Lei Zheng(德克萨斯大学) We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradi...
热度：68
2Groups-Keeping Solution Path Algorithm for Sparse Regression with Automatic Feature Grouping[自动特征分组稀疏回归的保组解路径算法]
黄恒(德克萨斯大学) Feature selection is one of the most important data mining research topics with many applications. In practical problems, features often have group st...
热度：24
黄恒(德克萨斯大学) Feature selection is one of the most important data mining research topics with many applications. In practical problems, features often have group st...
热度：24
3Bayesian entropy estimation for binary spike train data using parametric prior knowledge[基于参数先验知识的二值尖峰序列数据贝叶斯熵估计]
Evan W.Archer(德克萨斯大学) Shannon's entropy is a basic quantity in information theory, and a fundamental building block for the analysis of neural codes. Estimating the ent...
热度：16
Evan W.Archer(德克萨斯大学) Shannon's entropy is a basic quantity in information theory, and a fundamental building block for the analysis of neural codes. Estimating the ent...
热度：16
4Computational and mathematical challenges involved in estimating[推理中涉及的计算和数学挑战]
Tandy Warnow(德克萨斯大学) Phylogenetic inference presents enormous computational and mathematical challenges, but these are particularly exacerbated when dealing with very larg...
热度：76
Tandy Warnow(德克萨斯大学) Phylogenetic inference presents enormous computational and mathematical challenges, but these are particularly exacerbated when dealing with very larg...
热度：76
5Provable Matrix Completion using Alternating Minimization[交替极小化的可证矩阵完备化 ]
Praneeth Netrapalli(德克萨斯大学) Alternating minimization has emerged as a popular heuristic for large-scale machine learning problems involving low-rank matrices. However, there have...
热度：77
Praneeth Netrapalli(德克萨斯大学) Alternating minimization has emerged as a popular heuristic for large-scale machine learning problems involving low-rank matrices. However, there have...
热度：77
6The Qualitative Learner of Action and Perception, QLAP[行为和感知的定性学习，QLAP]
Benjamin Kuipers;Jonathan Mugan(德克萨斯大学) This video presents an introduction to the Qualitative Learner of Action and Perception, QLAP. QLAP autonomously learns a useful state abstraction and...
热度：47
Benjamin Kuipers;Jonathan Mugan(德克萨斯大学) This video presents an introduction to the Qualitative Learner of Action and Perception, QLAP. QLAP autonomously learns a useful state abstraction and...
热度：47
7A Framework for Simultaneous Co-clustering and Learning from Complex Data [一种同时聚类和复杂数据的学习框架]
Meghana Deodhar(德克萨斯大学) For difficult classification or regression problems, practitioners often segment the data into relatively homogenous groups and then build a model for...
热度：84
Meghana Deodhar(德克萨斯大学) For difficult classification or regression problems, practitioners often segment the data into relatively homogenous groups and then build a model for...
热度：84
8Practical RL: Representation, interaction, synthesis, and morality (PRISM)[实践RL：表现、互动、综合和道德（棱镜）]
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：27
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：27
9Words 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：38
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：38
10Object-Graphs for Context-Aware Category Discovery[上下文感知类别发现的对象图]
Yong Jae Lee(德克萨斯大学) How can knowing about some categories help us to dis- cover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for...
热度：42
Yong Jae Lee(德克萨斯大学) How can knowing about some categories help us to dis- cover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for...
热度：42