图 书 馆开课单位--耶路撒冷希伯来大学
21
22
23
24
25
26
27
28
29
30
21The Markovian Patch-Occupancy (MPO) framework in Community Ecology[群落生态学中的马尔科夫修补程序占用 (MPO) 框架]
Omri Allouch(耶路撒冷希伯来大学) Ecological research over the years has pointed to the existence of a wide spectrum of 'semi-universal' patterns of species diversity, found over very ...
热度：76
Omri Allouch(耶路撒冷希伯来大学) Ecological research over the years has pointed to the existence of a wide spectrum of 'semi-universal' patterns of species diversity, found over very ...
热度：76
22Trading Regret Rate for Computational Efficiency in Online Learning with Limited Feedback[有限反馈在线学习中计算效率的交易后悔率]
Shai Shalev-Shwartz(耶路撒冷希伯来大学) We study low regret algorithms for online learning with limited feedback, where there is an additional constraint on the computational power of the le...
热度：14
Shai Shalev-Shwartz(耶路撒冷希伯来大学) We study low regret algorithms for online learning with limited feedback, where there is an additional constraint on the computational power of the le...
热度：14
23Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies[收敛的消息传递算法推理在一般图凸自由能量]
Tamir Hazan(耶路撒冷希伯来大学) Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe fr...
热度：42
Tamir Hazan(耶路撒冷希伯来大学) Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe fr...
热度：42
24The price of bandit information in multiclass online classification[多类在线分类中Bandit信息的价值]
Amit Daniely(耶路撒冷希伯来大学) We consider two scenarios of multiclass online learning of a hypothesis class . In the full information scenario, the learner is exposed to instances ...
热度：53
Amit Daniely(耶路撒冷希伯来大学) We consider two scenarios of multiclass online learning of a hypothesis class . In the full information scenario, the learner is exposed to instances ...
热度：53
25A simple feature extraction for high dimensional image representations[用于高维图像表示的简单特征提取]
Amit Gruber(耶路撒冷希伯来大学) We investigate a method to find local clusters in low dimensional subspaces of high dimensional data, e.g. in high dimensional image descriptions. Usi...
热度：42
Amit Gruber(耶路撒冷希伯来大学) We investigate a method to find local clusters in low dimensional subspaces of high dimensional data, e.g. in high dimensional image descriptions. Usi...
热度：42
26What is the Optimal Number of Features? A learning theoretic perspective[功能的最佳数量是多少？从学习理论视角解读]
Amir Navot(耶路撒冷希伯来大学) In this paper we discuss the problem of feature selection for supervised learning from the standpoint of statistical machine learning. We inquire what...
热度：79
Amir Navot(耶路撒冷希伯来大学) In this paper we discuss the problem of feature selection for supervised learning from the standpoint of statistical machine learning. We inquire what...
热度：79
27The Sample-Computational Tradeoff[样本计算权衡 ]
Shai Shalev-Shwartz(耶路撒冷希伯来大学 ) When analyzing the error of a learning algorithm, it is common to decompose the error into approximation error (measuring how well the hypothesis cla...
热度：51
Shai Shalev-Shwartz(耶路撒冷希伯来大学 ) When analyzing the error of a learning algorithm, it is common to decompose the error into approximation error (measuring how well the hypothesis cla...
热度：51
28Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization[正则化损失最小化的随机双坐标上升法 ]
Shai Shalev-Shwartz(耶路撒冷希伯来大学) Stochastic Gradient Descent (SGD) has become popular for solving large scale supervised machine learning optimization problems such as SVM, due to the...
热度：162
Shai Shalev-Shwartz(耶路撒冷希伯来大学) Stochastic Gradient Descent (SGD) has become popular for solving large scale supervised machine learning optimization problems such as SVM, due to the...
热度：162
29What cannot be learned with Bethe Approximations[用贝斯近似法不能做到的东西]
Amir Globerson(耶路撒冷希伯来大学 ) We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the ...
热度：83
Amir Globerson(耶路撒冷希伯来大学 ) We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the ...
热度：83
30Old and New algorithm for Blind Deconvolution[盲反卷积的新旧算法 ]
Yair Weiss(耶路撒冷希伯来大学 ) I will discuss blind deconvolution algorithms that have been successfully used in the field of communications for several decades and how they can be ...
热度：60
Yair Weiss(耶路撒冷希伯来大学 ) I will discuss blind deconvolution algorithms that have been successfully used in the field of communications for several decades and how they can be ...
热度：60