ºÝºÝߣshows by User: guo_dong / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: guo_dong / Sun, 24 Jun 2018 06:04:24 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: guo_dong Convex optimization methods /slideshow/convex-optimization-methods/102877821 convexoptimizationmethods-180624060424
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͹ÓÅ»¯»ù±¾·½·¨Ð¡½á±Õ±Õ> Sun, 24 Jun 2018 06:04:24 GMT /slideshow/convex-optimization-methods/102877821 guo_dong@slideshare.net(guo_dong) Convex optimization methods guo_dong ͹ÓÅ»¯»ù±¾·½·¨Ð¡½á <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/convexoptimizationmethods-180624060424-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> ͹ÓÅ»¯»ù±¾·½·¨Ð¡½á
Convex optimization methods from Dong Guo
]]> 1559 4 https://cdn.slidesharecdn.com/ss_thumbnails/convexoptimizationmethods-180624060424-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 AlphaGo zero /slideshow/alphago-zero-102874771/102874771 alphagozero-180624040742
17Äêµ×ÔڵεÎÄÚ²¿µÄAlphaGo ZeroµÄ·ÖÏí]]>
17Äêµ×ÔڵεÎÄÚ²¿µÄAlphaGo ZeroµÄ·ÖÏí]]> Sun, 24 Jun 2018 04:07:42 GMT /slideshow/alphago-zero-102874771/102874771 guo_dong@slideshare.net(guo_dong) AlphaGo zero guo_dong 17Äêµ×ÔڵεÎÄÚ²¿µÄAlphaGo ZeroµÄ·ÖÏí <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/alphagozero-180624040742-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 17Äêµ×ÔڵεÎÄÚ²¿µÄAlphaGo ZeroµÄ·ÖÏí
AlphaGo zero from Dong Guo
]]> 350 3 https://cdn.slidesharecdn.com/ss_thumbnails/alphagozero-180624040742-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 DQN (Deep Q-Network) /slideshow/dqn-deep-qnetwork/102816268 dqn-180622130600
Reinforcement Learning]]>
Reinforcement Learning]]> Fri, 22 Jun 2018 13:06:00 GMT /slideshow/dqn-deep-qnetwork/102816268 guo_dong@slideshare.net(guo_dong) DQN (Deep Q-Network) guo_dong Reinforcement Learning <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dqn-180622130600-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Reinforcement Learning
DQN (Deep Q-Network) from Dong Guo
]]> 2870 4 https://cdn.slidesharecdn.com/ss_thumbnails/dqn-180622130600-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 »úÆ÷ѧϰ¸ÅÊö /slideshow/gai-51285948/51285948 machinelearningoverview-150805014137-lva1-app6892
Machine learning Overview]]>
Machine learning Overview]]> Wed, 05 Aug 2015 01:41:37 GMT /slideshow/gai-51285948/51285948 guo_dong@slideshare.net(guo_dong) »úÆ÷ѧϰ¸ÅÊö guo_dong Machine learning Overview <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/machinelearningoverview-150805014137-lva1-app6892-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Machine learning Overview
»úÆ÷ѧϰ¸ÅÊö from Dong Guo
]]> 2170 5 https://cdn.slidesharecdn.com/ss_thumbnails/machinelearningoverview-150805014137-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Expectation propagation /guo_dong/expectation-propagation-researchworkshop expectationpropagationresearchworkshop-131215193620-phpapp02
It's the deck for one Hulu internal machine learning workshop, which introduces the background, theory and application of expectation propagation method.]]>
It's the deck for one Hulu internal machine learning workshop, which introduces the background, theory and application of expectation propagation method.]]> Sun, 15 Dec 2013 19:36:20 GMT /guo_dong/expectation-propagation-researchworkshop guo_dong@slideshare.net(guo_dong) Expectation propagation guo_dong It's the deck for one Hulu internal machine learning workshop, which introduces the background, theory and application of expectation propagation method. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/expectationpropagationresearchworkshop-131215193620-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> It&#39;s the deck for one Hulu internal machine learning workshop, which introduces the background, theory and application of expectation propagation method.
Expectation propagation from Dong Guo
]]> 2184 7 https://cdn.slidesharecdn.com/ss_thumbnails/expectationpropagationresearchworkshop-131215193620-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Additive model and boosting tree /slideshow/additive-model-and-boosting-tree/14991112 additivemodelandboostingtree-121101220428-phpapp01
this is the forth slide for machine learning workshop in Hulu. Machine learning methods are summarized in the beginning of this slide, and boosting tree is introduced then. You are commended to try boosting tree when the feature number is not too much (&lt;1000)]]>
this is the forth slide for machine learning workshop in Hulu. Machine learning methods are summarized in the beginning of this slide, and boosting tree is introduced then. You are commended to try boosting tree when the feature number is not too much (&lt;1000)]]> Thu, 01 Nov 2012 22:04:26 GMT /slideshow/additive-model-and-boosting-tree/14991112 guo_dong@slideshare.net(guo_dong) Additive model and boosting tree guo_dong this is the forth slide for machine learning workshop in Hulu. Machine learning methods are summarized in the beginning of this slide, and boosting tree is introduced then. You are commended to try boosting tree when the feature number is not too much (&lt;1000) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/additivemodelandboostingtree-121101220428-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> this is the forth slide for machine learning workshop in Hulu. Machine learning methods are summarized in the beginning of this slide, and boosting tree is introduced then. You are commended to try boosting tree when the feature number is not too much (&amp;lt;1000)
Additive model and boosting tree from Dong Guo
]]> 2848 5 https://cdn.slidesharecdn.com/ss_thumbnails/additivemodelandboostingtree-121101220428-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Feature selection /guo_dong/feature-selection featureselection-120719061056-phpapp02
introduce typical methods used for feature selection, including filter, wrapper, subset selection]]>
introduce typical methods used for feature selection, including filter, wrapper, subset selection]]> Thu, 19 Jul 2012 06:10:52 GMT /guo_dong/feature-selection guo_dong@slideshare.net(guo_dong) Feature selection guo_dong introduce typical methods used for feature selection, including filter, wrapper, subset selection <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/featureselection-120719061056-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> introduce typical methods used for feature selection, including filter, wrapper, subset selection
Feature selection from Dong Guo
]]> 15135 7 https://cdn.slidesharecdn.com/ss_thumbnails/featureselection-120719061056-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Logistic Regression /slideshow/logistic-regressionpptx/13233653 talk-logisticregression-pptx-120607043844-phpapp01
introduce logistic regression, inference with maximize likelihood with gradient descent, compare L1 and L2 regularization, generalized linear model]]>
introduce logistic regression, inference with maximize likelihood with gradient descent, compare L1 and L2 regularization, generalized linear model]]> Thu, 07 Jun 2012 04:38:43 GMT /slideshow/logistic-regressionpptx/13233653 guo_dong@slideshare.net(guo_dong) Logistic Regression guo_dong introduce logistic regression, inference with maximize likelihood with gradient descent, compare L1 and L2 regularization, generalized linear model <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/talk-logisticregression-pptx-120607043844-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> introduce logistic regression, inference with maximize likelihood with gradient descent, compare L1 and L2 regularization, generalized linear model
Logistic Regression from Dong Guo
]]> 6027 8 https://cdn.slidesharecdn.com/ss_thumbnails/talk-logisticregression-pptx-120607043844-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Machine learning Introduction /slideshow/machine-learning-introduction/12715305 machinelearningintroduction-120427064838-phpapp01
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]]> Fri, 27 Apr 2012 06:48:37 GMT /slideshow/machine-learning-introduction/12715305 guo_dong@slideshare.net(guo_dong) Machine learning Introduction guo_dong <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/machinelearningintroduction-120427064838-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br>
Machine learning Introduction from Dong Guo
]]> 2134 6 https://cdn.slidesharecdn.com/ss_thumbnails/machinelearningintroduction-120427064838-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-guo_dong-48x48.jpg?cb=1543302202 Major in machine learning theory & application since 2008, and focus on leveraging it in online advertising, including Ad Targeting, Ad Inventory Projection & Mgmt., User modeling and experience optimization. Blog: http://dongguo.me ºÝºÝߣs: http://www.slideshare.net/guo_dong/ https://cdn.slidesharecdn.com/ss_thumbnails/convexoptimizationmethods-180624060424-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/convex-optimization-methods/102877821 Convex optimization me... https://cdn.slidesharecdn.com/ss_thumbnails/alphagozero-180624040742-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/alphago-zero-102874771/102874771 AlphaGo zero https://cdn.slidesharecdn.com/ss_thumbnails/dqn-180622130600-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/dqn-deep-qnetwork/102816268 DQN (Deep Q-Network)