�ݺ�ߣshows by User: ShuaiZhang33

�ݺ�ߣshows by User: ShuaiZhang33 / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: ShuaiZhang33 / Sat, 18 Aug 2018 03:20:43 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: ShuaiZhang33 Introduction to Random Walk /slideshow/introduction-to-random-walk/110363217 learninggroup-randomwalkshuai-180818032043
introduction to random walk and its applications on the machine learning]]>
introduction to random walk and its applications on the machine learning]]> Sat, 18 Aug 2018 03:20:43 GMT /slideshow/introduction-to-random-walk/110363217 ShuaiZhang33@slideshare.net(ShuaiZhang33) Introduction to Random Walk ShuaiZhang33 introduction to random walk and its applications on the machine learning <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/learninggroup-randomwalkshuai-180818032043-thumbnail.jpg?width=120&height=120&fit=bounds" /> introduction to random walk and its applications on the machine learning

Introduction to Random Walk from Shuai Zhang

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0 Learning group variational inference /slideshow/learning-group-variational-inference/100861401 learninggroup-variationalinference-20180525-180606045516
Introduction to Variational Inference]]>
Introduction to Variational Inference]]> Wed, 06 Jun 2018 04:55:16 GMT /slideshow/learning-group-variational-inference/100861401 ShuaiZhang33@slideshare.net(ShuaiZhang33) Learning group variational inference ShuaiZhang33 Introduction to Variational Inference <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/learninggroup-variationalinference-20180525-180606045516-thumbnail.jpg?width=120&height=120&fit=bounds" /> Introduction to Variational Inference

Learning group variational inference from Shuai Zhang

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0 Reading group nfm - 20170312 /slideshow/reading-group-nfm-20170312/90350714 readinggroup-nfm-20170312-180312053718
introduction of the factorization machine and neural factorization machine,]]>
introduction of the factorization machine and neural factorization machine,]]> Mon, 12 Mar 2018 05:37:18 GMT /slideshow/reading-group-nfm-20170312/90350714 ShuaiZhang33@slideshare.net(ShuaiZhang33) Reading group nfm - 20170312 ShuaiZhang33 introduction of the factorization machine and neural factorization machine, <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/readinggroup-nfm-20170312-180312053718-thumbnail.jpg?width=120&height=120&fit=bounds" /> introduction of the factorization machine and neural factorization machine,

Reading group nfm - 20170312 from Shuai Zhang

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0 Talk@rmit 09112017 /ShuaiZhang33/talkrmit-09112017 talkrmit-09112017-171109080525
With the explosive growth of online information, recommender system has been an effective tool to overcome information overload and promote sales. In recent years, deep learning's revolutionary advances in speech recognition, image analysis and natural language processing have gained significant attention. Meanwhile, recent studies also demonstrate its efficacy in coping with information retrieval and recommendation tasks. Applying deep learning techniques into recommender system has been gaining momentum due to its state-of-the-art performance. In this talk, I will present recent development of deep learning based recommender models and highlight some future challenges and open issues of this research field.]]>
With the explosive growth of online information, recommender system has been an effective tool to overcome information overload and promote sales. In recent years, deep learning's revolutionary advances in speech recognition, image analysis and natural language processing have gained significant attention. Meanwhile, recent studies also demonstrate its efficacy in coping with information retrieval and recommendation tasks. Applying deep learning techniques into recommender system has been gaining momentum due to its state-of-the-art performance. In this talk, I will present recent development of deep learning based recommender models and highlight some future challenges and open issues of this research field.]]> Thu, 09 Nov 2017 08:05:25 GMT /ShuaiZhang33/talkrmit-09112017 ShuaiZhang33@slideshare.net(ShuaiZhang33) Talk@rmit 09112017 ShuaiZhang33 With the explosive growth of online information, recommender system has been an effective tool to overcome information overload and promote sales. In recent years, deep learning's revolutionary advances in speech recognition, image analysis and natural language processing have gained significant attention. Meanwhile, recent studies also demonstrate its efficacy in coping with information retrieval and recommendation tasks. Applying deep learning techniques into recommender system has been gaining momentum due to its state-of-the-art performance. In this talk, I will present recent development of deep learning based recommender models and highlight some future challenges and open issues of this research field. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/talkrmit-09112017-171109080525-thumbnail.jpg?width=120&height=120&fit=bounds" /> With the explosive growth of online information, recommender system has been an effective tool to overcome information overload and promote sales. In recent years, deep learning's revolutionary advances in speech recognition, image analysis and natural language processing have gained significant attention. Meanwhile, recent studies also demonstrate its efficacy in coping with information retrieval and recommendation tasks. Applying deep learning techniques into recommender system has been gaining momentum due to its state-of-the-art performance. In this talk, I will present recent development of deep learning based recommender models and highlight some future challenges and open issues of this research field.

Talk@rmit 09112017 from Shuai Zhang

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0 Learning group em - 20171025 - copy /slideshow/learning-group-em-20171025-copy/81357682 learninggroup-em-20171025-copy-171030053813
EM algorithm and GMM]]>
EM algorithm and GMM]]> Mon, 30 Oct 2017 05:38:13 GMT /slideshow/learning-group-em-20171025-copy/81357682 ShuaiZhang33@slideshare.net(ShuaiZhang33) Learning group em - 20171025 - copy ShuaiZhang33 EM algorithm and GMM <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/learninggroup-em-20171025-copy-171030053813-thumbnail.jpg?width=120&height=120&fit=bounds" /> EM algorithm and GMM

Learning group em - 20171025 - copy from Shuai Zhang

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0 Learning group dssm - 20170605 /slideshow/learning-group-dssm-20170605/76885771 learninggroup-dssm-20170605-170613021328
deep similarity semantic model]]>
deep similarity semantic model]]> Tue, 13 Jun 2017 02:13:28 GMT /slideshow/learning-group-dssm-20170605/76885771 ShuaiZhang33@slideshare.net(ShuaiZhang33) Learning group dssm - 20170605 ShuaiZhang33 deep similarity semantic model <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/learninggroup-dssm-20170605-170613021328-thumbnail.jpg?width=120&height=120&fit=bounds" /> deep similarity semantic model

Learning group dssm - 20170605 from Shuai Zhang

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0 Reading group gan - 20170417 /slideshow/reading-group-gan-20170417/75370606 readinggroup-gan-20170417-170425005433
Introduction to generative adversarial networks]]>
Introduction to generative adversarial networks]]> Tue, 25 Apr 2017 00:54:32 GMT /slideshow/reading-group-gan-20170417/75370606 ShuaiZhang33@slideshare.net(ShuaiZhang33) Reading group gan - 20170417 ShuaiZhang33 Introduction to generative adversarial networks <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/readinggroup-gan-20170417-170425005433-thumbnail.jpg?width=120&height=120&fit=bounds" /> Introduction to generative adversarial networks

Reading group gan - 20170417 from Shuai Zhang

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0 Introduction to XGboost /slideshow/rg-xgboost20170306/73115984 rg-xgboost-20170306-170314022553
Introduction to XGboost, for more information please, visit: http://shuaizhang.tech/]]>
Introduction to XGboost, for more information please, visit: http://shuaizhang.tech/]]> Tue, 14 Mar 2017 02:25:52 GMT /slideshow/rg-xgboost20170306/73115984 ShuaiZhang33@slideshare.net(ShuaiZhang33) Introduction to XGboost ShuaiZhang33 Introduction to XGboost, for more information please, visit: http://shuaizhang.tech/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/rg-xgboost-20170306-170314022553-thumbnail.jpg?width=120&height=120&fit=bounds" /> Introduction to XGboost, for more information please, visit: http://shuaizhang.tech/

Introduction to XGboost from Shuai Zhang

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0 Introduction to CNN /slideshow/lg-cnn20170213/72051164 lg-cnn-20170213-170212095316
Introduction to Convolution Neural Network.]]>
Introduction to Convolution Neural Network.]]> Sun, 12 Feb 2017 09:53:16 GMT /slideshow/lg-cnn20170213/72051164 ShuaiZhang33@slideshare.net(ShuaiZhang33) Introduction to CNN ShuaiZhang33 Introduction to Convolution Neural Network. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lg-cnn-20170213-170212095316-thumbnail.jpg?width=120&height=120&fit=bounds" /> Introduction to Convolution Neural Network.

Introduction to CNN from Shuai Zhang

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0 https://public.slidesharecdn.com/v2/images/profile-picture.png https://cdn.slidesharecdn.com/ss_thumbnails/learninggroup-randomwalkshuai-180818032043-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/introduction-to-random-walk/110363217 Introduction to Random... https://cdn.slidesharecdn.com/ss_thumbnails/learninggroup-variationalinference-20180525-180606045516-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/learning-group-variational-inference/100861401 Learning group variat... https://cdn.slidesharecdn.com/ss_thumbnails/readinggroup-nfm-20170312-180312053718-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/reading-group-nfm-20170312/90350714 Reading group nfm - 2...