图 书 馆开课单位--沃森研究中心
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1Similarity Forests[相似森林]
Charu Aggarwa(沃森研究中心) Random forests are among the most successful methods used in data mining because of their extraordinary accuracy and effectiveness. However, their use...
热度：19
Charu Aggarwa(沃森研究中心) Random forests are among the most successful methods used in data mining because of their extraordinary accuracy and effectiveness. However, their use...
热度：19
2E‑tail Product Return Prediction via Hypergraph‑based Local Graph Cut[基于Hypergraph的局部图切割的E尾产品收益预测]
Yada Zhu(沃森研究中心) Recent decades have witnessed the rapid growth of E-commerce. In particular, E-tail has provided customers with great convenience by allowing them to ...
热度：26
Yada Zhu(沃森研究中心) Recent decades have witnessed the rapid growth of E-commerce. In particular, E-tail has provided customers with great convenience by allowing them to ...
热度：26
3Scalable Spectral Clustering Using Random Binning Features[使用随机二进制特征的可扩展光谱聚类]
Pin-Yu Chen(沃森研究中心) Spectral clustering is one of the most effective clustering approaches that capture hidden cluster structures in the data. However, it does not scale ...
热度：30
Pin-Yu Chen(沃森研究中心) Spectral clustering is one of the most effective clustering approaches that capture hidden cluster structures in the data. However, it does not scale ...
热度：30
4Large-scale Data Mining: MapReduce and Beyond[大规模数据挖掘：MapReduce及其超越]
Spiros Papadimitriou; Jimeng Sun; Rong Yan(沃森研究中心) Data are becoming available in unprecedented volumes. This difference in scale is difference in kind, presenting new opportunities. Map-reduce has dra...
热度：40
Spiros Papadimitriou; Jimeng Sun; Rong Yan(沃森研究中心) Data are becoming available in unprecedented volumes. This difference in scale is difference in kind, presenting new opportunities. Map-reduce has dra...
热度：40
5Closed-form Supervised Dimensionality Reduction with Generalized Linear Models[封闭形式的广义线性模型的监督降维]
Irina Rish(沃森研究中心) We propose a family of supervised dimensionality reduction (SDR) algorithms that combine feature extraction (dimensionality reduction) with learning a...
热度：41
Irina Rish(沃森研究中心) We propose a family of supervised dimensionality reduction (SDR) algorithms that combine feature extraction (dimensionality reduction) with learning a...
热度：41
6Hadoop-ML: An Infrastructure for the Rapid Implementation of Parallel Reusable Analytics[分布式计算机器语言：一个关于并行复用分析快速实现的基础设施]
Edwin Pednault(沃森研究中心) Hadoop is an open-source implementation of Google's Map-Reduce programming model. Over the past few years, it has evolved into a popular platform ...
热度：44
Edwin Pednault(沃森研究中心) Hadoop is an open-source implementation of Google's Map-Reduce programming model. Over the past few years, it has evolved into a popular platform ...
热度：44
7Creating and Using AI: Cyc and LarKC for Tourism, Language, Biology and Medicine[创建和使用人工智能：Cyc和LarKC的旅游，语言，生物学和医学]
Michael Witbrock(沃森研究中心) Creating and Using AI: Cyc and LarKC for Tourism, Language, Biology and Medicine
热度：42
Michael Witbrock(沃森研究中心) Creating and Using AI: Cyc and LarKC for Tourism, Language, Biology and Medicine
热度：42
8Multi-Armed Bandits with Betting[多武装土匪]
Alexandru Niculescu Mizil(沃森研究中心) We study an extension to the stochastic multiarmed bandit problem where the learner has a budget ofK “coins” it can use in each round. The...
热度：79
Alexandru Niculescu Mizil(沃森研究中心) We study an extension to the stochastic multiarmed bandit problem where the learner has a budget ofK “coins” it can use in each round. The...
热度：79
9Gradient Descent with Sparsification: An Iterative Algorithm for Sparse Recovery with Restricted Isometry Property[sparsifi阳离子梯度下降：有限制的等距性稀疏恢复的一种迭代算法]
Rahul Garg(沃森研究中心) In this paper, we present an algorithm for finding an s-sparse vector x that minimizes the square-error ∥y − Φx∥ 2 where Φ satisfies t...
热度：65
Rahul Garg(沃森研究中心) In this paper, we present an algorithm for finding an s-sparse vector x that minimizes the square-error ∥y − Φx∥ 2 where Φ satisfies t...
热度：65
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