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21. 发明申请

US20060190226A1 Systems and methods that utilize machine learning algorithms to facilitate assembly of aids vaccine cocktails 审中-公开
公开(公告)号：US20060190226A1
公开(公告)日：2006-08-24
申请号：US11324691
申请日：2005-12-30
申请人： Nebojsa Jojic , Vladimir Jojic , David Heckerman , Brendan Frey , Christopher Meek
发明人： Nebojsa Jojic , Vladimir Jojic , David Heckerman , Brendan Frey , Christopher Meek
IPC分类号： G06G7/48 , A61K39/21
CPC分类号： G16B40/00 , G16B10/00 , G16B20/00 , G16B30/00
摘要： The subject invention provides systems and methods that facilitate AIDS vaccine cocktail assembly via machine learning algorithms such as a cost function, a greedy algorithm, an expectation-maximization (EM) algorithm, etc. Such assembly can be utilized to generate vaccine cocktails for species of pathogens that evolve quickly under immune pressure of the host. For example, the systems and methods of the subject invention can be utilized to facilitate design of T cell vaccines for pathogens such HIV. In addition, the systems and methods of the subject invention can be utilized in connection with other applications, such as, for example, sequence alignment, motif discovery, classification, and recombination hot spot detection. The novel techniques described herein can provide for improvements over traditional approaches to designing vaccines by constructing vaccine cocktails with higher epitope coverage, for example, in comparison with cocktails of consensi, tree nodes and random strains from data.

22. 发明申请

US20060178861A1 Systems and methods that utilize machine learning algorithms to facilitate assembly of aids vaccine cocktails 有权
公开(公告)号：US20060178861A1
公开(公告)日：2006-08-10
申请号：US11324506
申请日：2005-12-30
申请人： Nebojsa Jojic , Vladimir Jojic , David Heckerman , Brendan Frey , Christopher Meek
发明人： Nebojsa Jojic , Vladimir Jojic , David Heckerman , Brendan Frey , Christopher Meek
IPC分类号： G06G7/48 , G06G7/58
CPC分类号： G06F19/22 , G06F19/14 , G06F19/18 , G06F19/24 , G06G7/48 , G06G7/58
摘要： The subject invention provides systems and methods that facilitate AIDS vaccine cocktail assembly via machine learning algorithms such as a cost function, a greedy algorithm, an expectation-maximization (EM) algorithm, etc. Such assembly can be utilized to generate vaccine cocktails for species of pathogens that evolve quickly under immune pressure of the host. For example, the systems and methods of the subject invention can be utilized to facilitate design of T cell vaccines for pathogens such HIV. In addition, the systems and methods of the subject invention can be utilized in connection with other applications, such as, for example, sequence alignment, motif discovery, classification, and recombination hot spot detection. The novel techniques described herein can provide for improvements over traditional approaches to designing vaccines by constructing vaccine cocktails with higher epitope coverage, for example, in comparison with cocktails of consensi, tree nodes and random strains from data.

23. 发明申请

US20060129395A1 Gradient learning for probabilistic ARMA time-series models 有权
标题翻译：概率ARMA时间序列模型的梯度学习
公开(公告)号：US20060129395A1
公开(公告)日：2006-06-15
申请号：US11011864
申请日：2004-12-14
申请人： Bo Thiesson , Christopher Meek
发明人： Bo Thiesson , Christopher Meek
IPC分类号： G10L15/12
CPC分类号： G06K9/00523
摘要： The subject invention leverages the conditional Gaussian (CG) nature of a continuous variable stochastic ARMAxp time series model to efficiently determine its parametric gradients. The determined gradients permit an easy means to construct a parametric structure for the time series model. This provides a gradient-based alternative to the expectation maximization (EM) process for learning parameters of the stochastic ARMAxp time series model. Thus, gradients for parameters can be computed and utilized with a gradient-based learning method for estimating the parameters. This allows values of continuous observations in a time series to be predicted utilizing the stochastic ARMAxp time series model, providing efficient and accurate predictions.
摘要翻译：本发明利用连续可变随机ARMA 时间序列模型的条件高斯（CG）特性来有效地确定其参数梯度。确定的梯度允许构建时间序列模型的参数结构的简单方法。这提供了用于学习随机ARMA时间序列模型的参数的期望最大化（EM）过程的基于梯度的替代。因此，可以使用基于梯度的学习方法来计算和利用参数梯度来估计参数。这允许使用随机ARMA 时间序列模型来预测时间序列中的连续观测值，从而提供有效和准确的预测。

24. 发明申请

US20060122889A1 System and method for managing a plurality of content items displayed in a particular placement position on a rendered page 审中-公开
标题翻译：用于管理在呈现的页面上的特定放置位置中显示的多个内容项目的系统和方法
公开(公告)号：US20060122889A1
公开(公告)日：2006-06-08
申请号：US10994877
申请日：2004-11-22
申请人： Brian Burdick , Christopher Meek , David Heckerman , David Chickering , Joshua Forman , Kevin Kornelson , Murali Vajjiravel , Rajeev Prasad , Raxit Kagalwala , Tarek Najm , Sachin Dhawan
发明人： Brian Burdick , Christopher Meek , David Heckerman , David Chickering , Joshua Forman , Kevin Kornelson , Murali Vajjiravel , Rajeev Prasad , Raxit Kagalwala , Tarek Najm , Sachin Dhawan
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0601
摘要： Systems and method for managing a plurality of content items designated for placement in a particular position on a rendered page are provided. Methods in accordance with the present invention include receiving a plurality of content items, determining an initial placement allocation frequency for each content item, collecting performance data for one or more of the content items, and determining at least one additional allocation frequency in accordance with the performance data collected. Methods of the present invention may further include randomly allocating placement of each of the content items in the particular position on the page in accordance with one of the respective initial and/or additional allocation frequency for each content item. Additionally, the present invention provides systems and methods for automatically managing a plurality of content items to be displayed in a particular position on a rendered page such that value to the content provider may be maximized.
摘要翻译：提供了用于管理指定用于放置在呈现页面上的特定位置的多个内容项的系统和方法。根据本发明的方法包括接收多个内容项目，确定每个内容项目的初始布局分配频率，收集一个或多个内容项目的演奏数据，以及根据所述内容项目确定至少一个附加分配频率收集性能数据。本发明的方法还可以包括根据每个内容项目的相应初始和/或附加分配频率之一随机分配每个内容项目在页面上的特定位置的布局。此外，本发明提供了用于自动管理要在呈现页面上的特定位置显示的多个内容项目的系统和方法，使得可以使对内容提供商的价值最大化。

25. 发明申请

US20060106710A1 Systems and methods for determining relative placement of content items on a rendered page 审中-公开
标题翻译：用于确定呈现页面上的内容项目的相对位置的系统和方法
公开(公告)号：US20060106710A1
公开(公告)日：2006-05-18
申请号：US10999586
申请日：2004-11-30
申请人： Christopher Meek , David Heckerman , David Chickering , Brian Burdick , Li Li , Murali Vajjiravel , Ying Li , Rajeev Prasad , Raxit Kagalwala , Tarek Najm , Sachin Dhawan
发明人： Christopher Meek , David Heckerman , David Chickering , Brian Burdick , Li Li , Murali Vajjiravel , Ying Li , Rajeev Prasad , Raxit Kagalwala , Tarek Najm , Sachin Dhawan
IPC分类号： G06Q40/00
CPC分类号： G06Q30/02 , G06Q30/0241 , G06Q30/0247 , G06Q30/0256 , G06Q30/0601 , G06Q30/08 , G06Q40/04
摘要： Systems and methods for determining the value of bids placed by content providers for placement positions on a page, e.g., a web page, rendered according to a given context, for instance, the search results listing for a particular query initiated on a search engine web site, are provided. Additionally, systems and methods are provided for determining placement of content items, e.g., advertisements and/or images, on a rendered page relative to other content items on the page based upon bid value.
摘要翻译：用于确定由内容提供商针对在给定上下文呈现的页面（例如，网页）上的放置位置的出价的价值的系统和方法，例如在搜索引擎网络上发起的特定查询的搜索结果列表现场提供。此外，提供了系统和方法，用于基于出价值，在相对于页面上的其他内容项目的呈现页面上确定内容项目（例如广告和/或图像）的放置。

26. 发明申请

US20050049987A1 Systems and methods for optimizing decision graph collaborative filtering 有权
标题翻译：优化决策图协同过滤的系统和方法
公开(公告)号：US20050049987A1
公开(公告)日：2005-03-03
申请号：US10654131
申请日：2003-09-03
申请人： Christopher Meek , David Chickering , Christopher Weare , Pradeep Gupta
发明人： Christopher Meek , David Chickering , Christopher Weare , Pradeep Gupta
IPC分类号： G06F17/00 , G06N5/02
CPC分类号： G06Q30/02 , G06Q10/10
摘要： The present invention provides collaborative filtering systems and methods employing default scores of decision graphs/trees to quickly create a top-n prediction list that can efficiently determine a user's interest in items. In one instance of the present invention, the list is refined by utilizing a variable maximum score algorithm and/or an invalidation list algorithm to insert items that score above an inclusion threshold set by a last item in the top-n prediction list. In another instance of the present invention, an invalidation list for a decision graph and/or decision tree is utilized to create a top-n prediction list. An algorithm employing default scores is then utilized to refine the top-n prediction list to insert items with default scores above an inclusion threshold set by a last item in the top-n prediction list.
摘要翻译：本发明提供协同过滤系统和采用默认分数的决策图/树的方法来快速地创建可以有效地确定用户对项目的兴趣的顶层预测列表。在本发明的一个实例中，通过使用可变最大分数算法和/或无效化列表算法来精简列表来插入在顶部n个预测列表中由最后一个项目设置的包含阈值以上的项目。在本发明的另一个实例中，利用用于决策图和/或决策树的无效列表来创建前n个预测列表。然后使用采用默认分数的算法来改进top-n预测列表，以将具有默认分数的项目插入高于由top-n预测列表中的最后项目设置的包含阈值的项目。

27. 发明申请

US20070270871A1 Surgical component fixation and method 有权
标题翻译：手术部件固定及方法
公开(公告)号：US20070270871A1
公开(公告)日：2007-11-22
申请号：US11405190
申请日：2006-04-17
申请人： Brian Byrd , Christopher Meek , Adam Sanford
发明人： Brian Byrd , Christopher Meek , Adam Sanford
IPC分类号： A61F5/00
CPC分类号： A61B17/154 , A61B17/8605
摘要： An apparatus is provided for attaching a surgical component to a bone at a surgical site. The apparatus includes an elongated pin and a cam mounted to the pin. The cam is engaged with the surgical component such that rotating the cam about the shaft axis changes the surgical component position relative to the bone.
摘要翻译：提供了一种用于将外科组件附接到外科手术部位的骨骼的装置。该装置包括细长的销和安装到该销的凸轮。凸轮与外科组件接合，使得凸轮围绕轴线的旋转改变外科组件相对于骨骼的位置。

28. 发明申请

US20070127818A1 SYSTEMS AND METHODS FOR ADAPTIVE HANDWRITING RECOGNITION 失效
标题翻译：用于自适应手写识别的系统和方法
公开(公告)号：US20070127818A1
公开(公告)日：2007-06-07
申请号：US11672458
申请日：2007-02-07
申请人： Bo Thiesson , Christopher Meek
发明人： Bo Thiesson , Christopher Meek
IPC分类号： G06K9/18
CPC分类号： G06K9/6292 , G06K9/222
摘要： The present invention utilizes generic and user-specific features of handwriting samples to provide adaptive handwriting recognition with a minimum level of user-specific enrollment data. By allowing generic and user-specific classifiers to facilitate in a recognition process, the features of a specific user's handwriting can be exploited to quickly ascertain characteristics of handwriting characters not yet entered by the user. Thus, new characters can be recognized without requiring a user to first enter that character as enrollment or “training” data. In one instance of the present invention, processing of generic features is accomplished by a generic classifier trained on multiple users. In another instance of the present invention, a user-specific classifier is employed to modify a generic classifier's classification as required to provide user-specific handwriting recognition.
摘要翻译：本发明利用手写样本的通用和用户特定的特征来提供具有最低级别的用户特定注册数据的自适应手写识别。通过允许通用和用户特定的分类器便于识别过程，可以利用特定用户手写的特征来快速确定用户尚未输入的手写字符的特征。因此，可以识别新的字符，而不需要用户首先将该字符输入作为注册或“训练”数据。在本发明的一个实例中，通用特征的处理由对多个用户进行训练的通用分类器来完成。在本发明的另一个实例中，使用用户特定的分类器根据需要修改通用分类器的分类以提供用户特定的手写识别。

29. 发明申请

US20070050357A1 Distributed reservoir sampling for web applications 有权
公开(公告)号：US20070050357A1
公开(公告)日：2007-03-01
申请号：US11212301
申请日：2005-08-26
申请人： David Chickering , Ashis Roy , Christopher Meek
发明人： David Chickering , Ashis Roy , Christopher Meek
IPC分类号： G06F17/30
CPC分类号： G06F17/30861 , Y10S707/99936
摘要： Random samples without replacement are extracted from a distributed set of items by leveraging techniques for aggregating sampled subsets of the distributed set. This provides a uniform random sample without replacement representative of the distributed set, allowing statistical information to be gleaned from extremely large sets of distributed information. Subset random samples without replacement are extracted from independent subsets of the distributed set of items. The subset random samples are then aggregated to provide a uniform random sample without replacement of a fixed size that is representative of a distributed set of items of unknown size. In one instance, a multivariate hyper-geometric distribution is sampled by breaking up the multivariate hyper-geometric distribution into a set of univariate hyper-geometric distributions. Individual items of a uniform random sample without replacement are then determined utilizing a normal approximation of the univariate hyper-geometric distributions and a finite population correction factor.

30. 发明申请

US20050149052A1 Offset orthopaedic driver and method 审中-公开
标题翻译：矫正矫形器和方法
公开(公告)号：US20050149052A1
公开(公告)日：2005-07-07
申请号：US10750439
申请日：2003-12-31
申请人： Christopher Meek
发明人： Christopher Meek
IPC分类号： A61B17/88 , A61F2/00 , A61F2/30 , A61F2/38 , A61F2/46 , A61B17/58
CPC分类号： A61F2/3859 , A61B17/8875 , A61F2/30734 , A61F2/4637 , A61F2002/30131 , A61F2002/30433 , A61F2002/30438 , A61F2002/30736 , A61F2002/30797 , A61F2002/30886 , A61F2002/4624 , A61F2002/4638 , A61F2220/0041 , A61F2230/0013
摘要： A driver and method are presented for driving fasteners inside of an orthopaedic implant.
摘要翻译：提出了用于驱动矫形外科植入物内的紧固件的驱动器和方法。

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