1. Bing 学术


    微软学术,由微软必应团队联合研究院打造的免费学术搜索产品,旨在为广大研究人员提供海量的学术资源 ...

  2. [1606.00318] Discovering Phase Transitions with Unsupervised Learning - arXiv.org e-Print archive


    Abstract: Unsupervised learning is a discipline of machine learning which aims at discovering patterns in big data sets or classifying the data into several categories without being trained explicitly. We show th…

  3. M3RSM: Many-To-Many Multi-Resolution Scan Matching


    M3RSM: Many-to-Many Multi-Resolution Scan Matching Edwin Olson 1 Abstract We describe a new multi-resolution scan matching method that makes exhaustive (and thus local-minimum-proof)

  4. Collaborative Deep Learning for Recommender Systems - arXiv


    Collaborative Deep Learning for Recommender Systems Hao Wang Hong Kong University of Science and Technology hwangaz@cse.ust.hk Naiyan Wang Hong Kong University of

  5. Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning - University of California, San Diego


    the car will likely cross the lane boundary, then we must presume he/she intends a lane change. Kuge et. al. [4] de-veloped Hidden Markov Models (HMMs) using observa-

  6. Empathy and Masculinity in Harper Lee's to Kill a Mockingbird


    Abstract. Harper Lee’s To Kill a Mockingbird illustrates a troubled relationship between lawyering and empathy and between empathy and masculinity.

  7. Performance analysis and optimization of organic Rankine cycle (ORC) for waste heat recovery

    users.ugent.be/~mvbelleg/literatuur SCHX - Stijn Daelman/ORCNext...

    Performance analysis and optimization of organic Rankine cycle (ORC) for waste heat recovery Donghong Wei *, Xuesheng Lu, Zhen Lu, Jianming Gu Institute of Refrigeration and Cryogenics, School of Mechani…

  8. 学术大师聚集地,人才培养典范——清华大学媒体与网络 ...


    为了了解清华大学联合实验室的情况,《计算机教育》杂志拜访了清华大学计算机系党委书记兼常务副主任、“华大学媒体与网络技术教育部-微软联合实验室”主任杨士强 ...

  9. Learning with Kernels - dl.acm.org


    From the Publisher: In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM).

  10. www.ncbi.nlm.nih.gov


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