开课单位--康奈尔大学
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ABC-Boost: Adaptive Base Class Boost for Multi-Class Classification[ABC-Boost:用于多类分类的自适应基类升压]
Ping Li(康奈尔大学) We propose ABC-Boost (Adaptive Base Class Boost) for multi-class classification and present ABC-MART, an implementation of ABC-Boost. The original MA...
热度:229
Ping Li(康奈尔大学) We propose ABC-Boost (Adaptive Base Class Boost) for multi-class classification and present ABC-MART, an implementation of ABC-Boost. The original MA...
热度:229
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Learning Prediction Suffix Trees with Winnow[用Winnow学习预测后缀树]
Nikos Karampatziakis(康奈尔大学) Prediction suffix trees (PSTs) are a popular tool for modeling sequences and have been successfully applied in many domains such as compression and la...
热度:36
Nikos Karampatziakis(康奈尔大学) Prediction suffix trees (PSTs) are a popular tool for modeling sequences and have been successfully applied in many domains such as compression and la...
热度:36
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Fast Solvers and Efficient Implementations for Distance Metric Learning[远程度量学习的快速求解和有效实现]
Kilian Weinberger(康奈尔大学) In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed frame...
热度:97
Kilian Weinberger(康奈尔大学) In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed frame...
热度:97
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Detecting Statistical Interactions with Additive Groves of Trees[用树的附加树枝检测统计相互作用]
Daria Sorokina(康奈尔大学) Discovering additive structure is an important step towards understanding a complex multi-dimensional function because it allows the function to be ex...
热度:79
Daria Sorokina(康奈尔大学) Discovering additive structure is an important step towards understanding a complex multi-dimensional function because it allows the function to be ex...
热度:79
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Learning Diverse Rankings with Multi-Armed Bandits[学习多种强化学习的不同排名]
Robert Kleinberg(康奈尔大学) Algorithms for learning to rank Web documents usually assume a document's relevance is independent of other documents. This leads to learned ranking f...
热度:76
Robert Kleinberg(康奈尔大学) Algorithms for learning to rank Web documents usually assume a document's relevance is independent of other documents. This leads to learned ranking f...
热度:76
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An Empirical Evaluation of Supervised Learning in High Dimensions[高维监督学习的实证评价]
Nikos Karampatziakis(康奈尔大学) In this paper we perform an empirical evaluation of supervised learning methods on high dimensional data. We evaluate learning performance on three me...
热度:86
Nikos Karampatziakis(康奈尔大学) In this paper we perform an empirical evaluation of supervised learning methods on high dimensional data. We evaluate learning performance on three me...
热度:86
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Training Structural SVMs when Exact Inference is Intractable[当精确推理难以解决时训练结构支持向量机]
Thomas Finley(康奈尔大学) While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex ...
热度:50
Thomas Finley(康奈尔大学) While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex ...
热度:50
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Privacy and Background Knowledge[隐私和背景知识]
Johannes Gehrke(康奈尔大学) The digitization of our daily lives has led to an explosion in the collection of data by governments, corporations, and individuals. Protection of con...
热度:42
Johannes Gehrke(康奈尔大学) The digitization of our daily lives has led to an explosion in the collection of data by governments, corporations, and individuals. Protection of con...
热度:42
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Sparse Kernel SVMs via Cutting-Plane Training[通过切割平面训练的核心SVM训练改善稀疏性]
Chun-Nam Yu(康奈尔大学) We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors...
热度:81
Chun-Nam Yu(康奈尔大学) We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors...
热度:81
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Identifying the Original Contribution of a Document via Language Modeling[通过语言建模识别文档的原始思想贡献]
Benyah Shaparenko(康奈尔大学) One major goal of text mining is to provide automatic methods to help humans grasp the key ideas in ever-increasing text corpora. To this effect, we p...
热度:45
Benyah Shaparenko(康奈尔大学) One major goal of text mining is to provide automatic methods to help humans grasp the key ideas in ever-increasing text corpora. To this effect, we p...
热度:45