图 书 馆开课单位--耶路撒冷希伯来大学
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31Online Learning in The Manifold of Low-Rank Matrices[低秩矩阵流中的在线学习]
Uri Shalit(耶路撒冷希伯来大学) When learning models that are represented in matrix forms, enforcing a low-rank constraint can dramatically improve the memory and run time complexity...
热度：86
Uri Shalit(耶路撒冷希伯来大学) When learning models that are represented in matrix forms, enforcing a low-rank constraint can dramatically improve the memory and run time complexity...
热度：86
32Graphical Models and Applications[图形模型和应用]
Yair Weiss(耶路撒冷希伯来大学) Compressed sensing is a recent set of mathematical results showing that sparse signals can be exactly reconstructed from a small number of linear meas...
热度：35
Yair Weiss(耶路撒冷希伯来大学) Compressed sensing is a recent set of mathematical results showing that sparse signals can be exactly reconstructed from a small number of linear meas...
热度：35
33Online Learning with Kernels[使用内核进行在线学习]
Yoram Singer(耶路撒冷希伯来大学) Online learning is concerned with the task of making decisions on-the-fly as observations are received. We describe and analyze several online learnin...
热度：123
Yoram Singer(耶路撒冷希伯来大学) Online learning is concerned with the task of making decisions on-the-fly as observations are received. We describe and analyze several online learnin...
热度：123
34An Efficient Online Algorithm for Hierarchical Phoneme Classification[一种高效的分层音素分类在线算法]
Joseph Keshet(耶路撒冷希伯来大学) We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure...
热度：65
Joseph Keshet(耶路撒冷希伯来大学) We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure...
热度：65
35Honest Compressions and Their Application to Compression Schemes[诚实压缩及其在压缩方案中的应用]
Roi Livni(耶路撒冷希伯来大学) The existence of a compression scheme for every concept class with bounded VC-dimension is one of the oldest open problems in statistical learning the...
热度：31
Roi Livni(耶路撒冷希伯来大学) The existence of a compression scheme for every concept class with bounded VC-dimension is one of the oldest open problems in statistical learning the...
热度：31
36Non-Genetic Individuality in a Predator-Prey system[捕食者-被捕食系统中的非遗传个体]
Nathalie Questembert-Balaban(耶路撒冷希伯来大学) Isogenic bacteria can exhibit a range of phenotypes, even in homogeneous environmental conditions. Such non-genetic individuality has been observed in...
热度：85
Nathalie Questembert-Balaban(耶路撒冷希伯来大学) Isogenic bacteria can exhibit a range of phenotypes, even in homogeneous environmental conditions. Such non-genetic individuality has been observed in...
热度：85
37Multiclass Learning Approaches: A Theoretical Comparison with Implications[多类别学习方法：理论上与启示的比较]
Amit Daniely(耶路撒冷希伯来大学) We theoretically analyze and compare the following five popular multiclass classification methods: One vs. All, All Pairs, Tree-based classifiers, Err...
热度：58
Amit Daniely(耶路撒冷希伯来大学) We theoretically analyze and compare the following five popular multiclass classification methods: One vs. All, All Pairs, Tree-based classifiers, Err...
热度：58
38On probabilistic hypergraph matching[概率超图匹配]
Amnon Shashua(耶路撒冷希伯来大学) We consider the problem of finding a matching between two sets of features, given complex relations among them, going beyond pairwise. We derive the h...
热度：107
Amnon Shashua(耶路撒冷希伯来大学) We consider the problem of finding a matching between two sets of features, given complex relations among them, going beyond pairwise. We derive the h...
热度：107
39Efficient Projections onto the L1-Ball for Learning in High Dimensions[L1-Ball上的高效投影用于高维学习]
Yoram Singer(耶路撒冷希伯来大学) We describe efficient algorithms for projecting a vector onto the L1-ball. We present two methods for projection. The first performs exact projection ...
热度：72
Yoram Singer(耶路撒冷希伯来大学) We describe efficient algorithms for projecting a vector onto the L1-ball. We present two methods for projection. The first performs exact projection ...
热度：72
40Learning Distance Function by Coding Similarity[编码相似度学习距离函数]
Rioe Kliper(耶路撒冷希伯来大学) We consider the problem of learning a similarity function from a set of positive equivalence constraints, i.e. "similar" point pairs. We def...
热度：48
Rioe Kliper(耶路撒冷希伯来大学) We consider the problem of learning a similarity function from a set of positive equivalence constraints, i.e. "similar" point pairs. We def...
热度：48