图 书 馆开课单位--魏茨曼科学研究所
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11Using linking features in learning non-parametric part models[在学习非参数零件模型中的链接特征]
Stefan Carlsson;Antonio Torralba;Leonid Karlinsky(魏茨曼科学研究所) We present an approach to the detection of parts of highly deformable objects, such as the human body. Instead of using kinematic constraints on relat...
热度：24
Stefan Carlsson;Antonio Torralba;Leonid Karlinsky(魏茨曼科学研究所) We present an approach to the detection of parts of highly deformable objects, such as the human body. Instead of using kinematic constraints on relat...
热度：24
12Efficient Online Learning via Randomized Rounding[通过随机舍入实现高效的在线学习]
Ohad Shamir(魏茨曼科学研究所) Most online algorithms used in machine learning today are based on variants of mirror descent or follow-the-leader. In this paper, we present an onlin...
热度：91
Ohad Shamir(魏茨曼科学研究所) Most online algorithms used in machine learning today are based on variants of mirror descent or follow-the-leader. In this paper, we present an onlin...
热度：91
13Diffusion Maps, Spectral Clustering and Reaction Coordinates of Dynamical Systems[动力系统的扩散映射，谱聚类和反应坐标]
Boaz Nadler(魏茨曼科学研究所) A central problem in data analysis is the low dimensional representation of high dimensional data, and the concise description of its underlying geome...
热度：129
Boaz Nadler(魏茨曼科学研究所) A central problem in data analysis is the low dimensional representation of high dimensional data, and the concise description of its underlying geome...
热度：129
14A Universal Kernel for Learning Regular Languages[学习常规语言的通用核心]
Leonid Kontorovich(魏茨曼科学研究所) We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conject...
热度：18
Leonid Kontorovich(魏茨曼科学研究所) We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conject...
热度：18
15Collaborative Filtering with the Trace Norm: Learning, Bounding, and Transducing [跟踪规范的协作过滤:学习、边界和转换]
Ohad Shamir(魏茨曼科学研究所) Trace-norm regularization is a widely-used and successful approach for collaborative filtering and matrix completion. However, its theoretical unders...
热度：86
Ohad Shamir(魏茨曼科学研究所) Trace-norm regularization is a widely-used and successful approach for collaborative filtering and matrix completion. However, its theoretical unders...
热度：86
16A metric notion of dimension and its applications to learning[维度的度量概念及其在学习中的应用]
Robert Krauthgamer(魏茨曼科学研究所) Let us define the dimension of a metric space as the minimum k>0 such that every ball in the metric space can be covered by 2^k balls of half the r...
热度：84
Robert Krauthgamer(魏茨曼科学研究所) Let us define the dimension of a metric space as the minimum k>0 such that every ball in the metric space can be covered by 2^k balls of half the r...
热度：84
17Learning to Classify with Missing and Corrupted Features[学习使用缺失和损坏的功能进行分类]
Ohad Shamir(魏茨曼科学研究所) After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in t...
热度：60
Ohad Shamir(魏茨曼科学研究所) After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in t...
热度：60
18From Bandits to Experts : On the Value of More Information[从土匪到专家：更多信息的价值]
Ohad Shamir(魏茨曼科学研究所) Learning from Experts and Multi-armed Bandits are two of the most common settings studied in online learning. Whereas the first setting assumes that t...
热度：32
Ohad Shamir(魏茨曼科学研究所) Learning from Experts and Multi-armed Bandits are two of the most common settings studied in online learning. Whereas the first setting assumes that t...
热度：32
19“Clustering by Composition” for Unsupervised Discovery of Image Categories[“按构图聚类”用于无监督发现图像类别]
Tinne Tuytelaars, Alon Faktor, Serge J. Belongie(魏茨曼科学研究所) We define a good image cluster as one in which images can be easily composed (like a puzzle) using pieces from each other, while are difficult to comp...
热度：51
Tinne Tuytelaars, Alon Faktor, Serge J. Belongie(魏茨曼科学研究所) We define a good image cluster as one in which images can be easily composed (like a puzzle) using pieces from each other, while are difficult to comp...
热度：51
20The chains model for detecting parts by their context[基于上下文的零件检测链模型]
Leonid Karlinsky(魏茨曼科学研究所) Detecting an object part relies on two sources of information - the appearance of the part itself, and the context supplied by surrounding parts. In t...
热度：60
Leonid Karlinsky(魏茨曼科学研究所) Detecting an object part relies on two sources of information - the appearance of the part itself, and the context supplied by surrounding parts. In t...
热度：60