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1. 发明授权

US08260655B2 Price optimization with robust learning constraint 有权
标题翻译：价格优化与强大的学习约束
公开(公告)号：US08260655B2
公开(公告)日：2012-09-04
申请号：US12792124
申请日：2010-06-02
申请人： Christopher R. Dance , Onno Zoeter
发明人： Christopher R. Dance , Onno Zoeter
IPC分类号： G06Q10/00 , G06Q30/00 , G06F15/18
CPC分类号： G06Q30/0283 , G06Q30/0201
摘要： A valuation optimization method includes generating offeree decision information (buyer decision information, by way of illustrative example) by presenting a sequence of mechanisms to a sequence of offerees wherein the mechanisms comprise menus of transaction offers (sale offer menus, by way of illustrative example). Actual transactions (sale transactions, by way of illustrative example) are conducted responsive to acceptances of transaction offers by buyers. At a selected time in the generating, an offeree valuation distribution belief and the current mechanism are updated optimize an offeree's utility. The offeree's utility comprises an offeree's utility function constrained by a robust learning constraint computed based on a local differential of an earlier offeree's utility function with respect to the earlier offeree's valuation.
摘要翻译：评估优化方法包括通过向参与者序列呈现机制序列来产生违约决定信息（作为说明性示例的买方决定信息），其中机制包括交易提供的菜单（销售提供菜单，作为说明性示例）。实际交易（销售交易，作为说明性的例子）是响应买家对交易报价的接受。在生成的选定时间，受委派的估值分配信念和当前机制被更新优化了受访者的效用。受委人的实用程序包括受约束的效用函数，受到基于较早受访者效用函数的局部差异计算的强大的学习约束，相对于较早的受访者的估值。

2. 发明授权

US08190550B2 Split variational inference 有权
标题翻译：分裂变分推理
公开(公告)号：US08190550B2
公开(公告)日：2012-05-29
申请号：US12481802
申请日：2009-06-10
申请人： Guillaume M. Bouchard , Onno Zoeter
发明人： Guillaume M. Bouchard , Onno Zoeter
IPC分类号： G06F17/10 , G06F17/17 , G06F17/18
CPC分类号： G06F17/10 , G06K9/6221
摘要： A method comprises: partitioning a region of interest into a plurality of soft bin regions that span the region of interest; estimating an integral over each soft bin region of a function defined over the region of interest; and outputting a value equal to or derived from the sum of the estimated integrals over the soft bin regions spanning the region of interest. The method may further comprise: integrating a Bayesian theorem function using the partitioning, estimating, and outputting operations, and classifying an object to be classified using a classifier trained using the Bayesian machine learning. The method may further comprise performing optimal control by iteratively minimizing a controlled system cost function to determine optimized control inputs using the partitioning, estimating, and outputting with the function equal to the controlled system cost function having the selected control inputs, and controlling the controlled system using the optimized control inputs.
摘要翻译：一种方法包括：将感兴趣区域划分成跨越感兴趣区域的多个软仓区域; 估计在感兴趣区域上定义的函数的每个软仓区域上的积分; 并且在跨越感兴趣区域的软仓区域上输出等于或从所估计的积分的总和导出的值。该方法还可以包括：使用分区，估计和输出操作来整合贝叶斯定理函数，并且使用使用贝叶斯机器学习训练的分类器对要分类的对象进行分类。该方法还可以包括通过迭代地最小化受控系统成本函数来执行最优控制，以使用等于具有所选择的控制输入的受控系统成本函数的功能进行分区，估计和输出来确定优化的控制输入，并且控制受控系统使用优化的控制输入。

3. 发明申请

US20110302041A1 LIMITED LOTTERY INSURANCE 有权
标题翻译：有限保险
公开(公告)号：US20110302041A1
公开(公告)日：2011-12-08
申请号：US12792254
申请日：2010-06-02
申请人： Christopher R. Dance , Onno Zoeter , Gillaume M. Bouchard
发明人： Christopher R. Dance , Onno Zoeter , Gillaume M. Bouchard
IPC分类号： G06Q30/00 , G06Q10/00
CPC分类号： G06Q30/0283 , G06Q30/0601
摘要： A system and method for conducting a lottery for at least one item are provided. The method includes, for each of a plurality of buyers, receiving a buyer's declared valuation for each of at least one item being offered in a lottery by a seller, the item having an assigned non-deterministic probability of being allocated to the buyer, providing insured prices for outcomes of the lottery which are a function of the buyer's declared valuation of the at least one item, randomly drawing an allocation of each of the at least one item to a respective one of the buyers, based on its assigned non-deterministic probability, and allocating the insured prices to the buyers based on respective outcomes of the random drawing.
摘要翻译：提供了用于至少一个项目进行彩票的系统和方法。该方法包括对于多个购买者中的每一个，由卖方接收买方对于在彩票中提供的至少一个项目中的每一个的所宣告的估价，该项目具有分配给买方的分配的非确定性概率，提供所述彩票的结果的保险价格是买方对所述至少一个项目的已宣布估价值的函数，其随机地将所述至少一个项目中的每一个分配给相应的一个买方，基于其分配的非确定性概率，并根据随机抽签的各自结果将保险价格分配给买方。

4. 发明申请

US20110302013A1 MULTI-DIMENSIONAL PRICE DETERMINATION 有权
标题翻译：多维价格决定
公开(公告)号：US20110302013A1
公开(公告)日：2011-12-08
申请号：US12792267
申请日：2010-06-02
申请人： Christopher R. Dance , Onno Zoeter
发明人： Christopher R. Dance , Onno Zoeter
IPC分类号： G06Q10/00 , G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0217 , G06Q30/0283 , G06Q30/0631 , G06Q30/0641
摘要： A system and method are provided. The method includes establishing a current belief about the multidimensional distribution of buyers' valuations for at least one item, and, based on the current belief, proposing at least one pricing mechanism, each pricing mechanism establishing a price for the at least one item. Observed buyers' responses to at least one of the set of proposed pricing mechanisms are stored. Region censored updates to the belief about the multidimensional distribution of buyers' valuations are conducted, based on the observed responses, to generate a new belief about the multidimensional distribution of buyers' valuations. Based on the new belief, a pricing mechanism establishing a price for the at least one item is proposed, that is expected to improve a seller's welfare under the new belief, relative to the originally proposed mechanism or mechanisms.
摘要翻译：提供了一种系统和方法。该方法包括建立目前关于至少一个项目的买方估价的多维分布的信念，并且基于目前的观点，提出至少一个定价机制，每个定价机制为至少一个项目建立价格。观察到的买家对至少一组提出的定价机制的回应被存储。根据观察到的反应，区域审查了对买方估值的多维分布的信念的更新，以产生对买方估值的多维分布的新观点。基于新的观点，提出了建立至少一个项目价格的定价机制，相对于原来提出的机制或机制，预期会提高卖方在新信念下的福利。

5. 发明授权

US08924315B2 Multi-task learning using bayesian model with enforced sparsity and leveraging of task correlations 有权
标题翻译：使用具有强制稀疏性和利用任务相关性的贝叶斯模型进行多任务学习
公开(公告)号：US08924315B2
公开(公告)日：2014-12-30
申请号：US13324060
申请日：2011-12-13
申请人： Cedric Archambeau , Shengbo Guo , Onno Zoeter , Jean-Marc Andreoli
发明人： Cedric Archambeau , Shengbo Guo , Onno Zoeter , Jean-Marc Andreoli
IPC分类号： G06F15/18 , G06F19/24
CPC分类号： G06N7/005 , G06N3/08
摘要： Multi-task regression or classification includes optimizing parameters of a Bayesian model representing relationships between D features and P tasks, where D≧1 and P≧1, respective to training data comprising sets of values for the D features annotated with values for the P tasks. The Bayesian model includes a matrix-variate prior having features and tasks dimensions of dimensionality D and P respectively. The matrix-variate prior is partitioned into a plurality of blocks, and the optimizing of parameters of the Bayesian model includes inferring prior distributions for the blocks of the matrix-variate prior that induce sparseness of the plurality of blocks. Values of the P tasks are predicted for a set of input values for the D features using the optimized Bayesian model. The optimizing also includes decomposing the matrix-variate prior into a product of matrices including a matrix of reduced rank in the tasks dimension that encodes correlations between tasks.
摘要翻译：多任务回归或分类包括优化表示D特征和P任务之间的关系的贝叶斯模型的参数，其中D≥1和P≥1，分别对应于包含P任务的值所注明的D特征值的值的训练数据。贝叶斯模型包括先前具有维度D和P的特征和任务维度的矩阵变量。矩阵变量先验被划分成多个块，并且贝叶斯模型的参数的优化包括推导出先前分布的矩阵变量的块，从而引起多个块的稀疏。使用优化的贝叶斯模型，为D特征的一组输入值预测P任务的值。优化还包括将矩阵变量分解成矩阵乘积，包括在任务维度中编码任务之间的相关性的减少秩的矩阵。

6. 发明授权

US07958004B2 Methods for supply chain management 有权
标题翻译：供应链管理方法
公开(公告)号：US07958004B2
公开(公告)日：2011-06-07
申请号：US12570430
申请日：2009-09-30
申请人： Christopher R. Dance , Onno Zoeter
发明人： Christopher R. Dance , Onno Zoeter
IPC分类号： G06F17/30
CPC分类号： G06Q10/087 , G06Q30/0202
摘要： According to various embodiments, the present teachings include inventory control policies that are defined in terms of functions of aggregate cost rates, involving thresholds Ω and an order-up-to point S. An embodiment of the present teachings includes a method. The method includes tracking an inventory position of each of the plurality of items by a logistics network and determining an item cost rate for each of the plurality of items based on the tracked inventory position. The method also includes determining an aggregate cost rate for the plurality of items based on the determined item cost rates, comparing the aggregate cost rate with a cost rate threshold Ω, and ordering the plurality of items to an order-up-to point S if the compared aggregate cost rate is greater than or equal to the cost rate threshold Ω.
摘要翻译：根据各种实施例，本教导包括根据总成本率的功能定义的库存控制策略，涉及阈值＆OHgr; 和点到点S.本教导的实施例包括一种方法。所述方法包括：通过物流网络跟踪所述多个物品中的每一个的库存位置，并基于跟踪的库存位置确定所述多个料品中的每一个的料品成本率。该方法还包括基于确定的项目成本率确定多个项目的总成本率，将总成本率与成本率阈值＆amp; OHgr进行比较，并将多个项目排序到点到点S 如果比较的总成本率大于或等于成本率阈值＆OHgr;

7. 发明申请

US20100318490A1 SPLIT VARIATIONAL INFERENCE 有权
标题翻译：分散变化影响
公开(公告)号：US20100318490A1
公开(公告)日：2010-12-16
申请号：US12481802
申请日：2009-06-10
申请人： Guillaume M. Bouchard , Onno Zoeter
发明人： Guillaume M. Bouchard , Onno Zoeter
IPC分类号： G06N7/02
CPC分类号： G06F17/10 , G06K9/6221
摘要： A method comprises: partitioning a region of interest into a plurality of soft bin regions that span the region of interest; estimating an integral over each soft bin region of a function defined over the region of interest; and outputting a value equal to or derived from the sum of the estimated integrals over the soft bin regions spanning the region of interest. The method may further comprise: integrating a Bayesian theorem function using the partitioning, estimating, and outputting operations, and classifying an object to be classified using a classifier trained using the Bayesian machine learning. The method may further comprise performing optimal control by iteratively minimizing a controlled system cost function to determine optimized control inputs using the partitioning, estimating, and outputting with the function equal to the controlled system cost function having the selected control inputs, and controlling the controlled system using the optimized control inputs.
摘要翻译：一种方法包括：将感兴趣区域划分成跨越感兴趣区域的多个软仓区域; 估计在感兴趣区域上定义的函数的每个软仓区域上的积分; 并且在跨越感兴趣区域的软仓区域上输出等于或从所估计的积分的总和导出的值。该方法还可以包括：使用分区，估计和输出操作来整合贝叶斯定理函数，并且使用使用贝叶斯机器学习训练的分类器对要分类的对象进行分类。该方法还可以包括通过迭代地最小化受控系统成本函数来执行最优控制，以使用等于具有所选择的控制输入的受控系统成本函数的功能进行分区，估计和输出来确定优化的控制输入，并且控制受控系统使用优化的控制输入。

8. 发明授权

US08538833B2 Method for estimation of a payment for an existing report based on subsequent reports which provides incentives for reporters to report truthfully 有权
标题翻译：根据后续报告估计现有报告的付款方式，为报告员提供激励措施
公开(公告)号：US08538833B2
公开(公告)日：2013-09-17
申请号：US12695757
申请日：2010-01-28
申请人： Christopher R. Dance , Onno Zoeter , Yu-An Sun , Venkatesh Rao
发明人： Christopher R. Dance , Onno Zoeter , Yu-An Sun , Venkatesh Rao
IPC分类号： G06Q99/00
CPC分类号： G06Q10/00 , G06Q20/102 , G06Q20/20 , G06Q30/0218 , G06Q30/0282 , G06Q30/0283 , G06Q99/00
摘要： A method and apparatus for paying for an existing report are provided. In the method, an existing report for which a first structure of entities is identified is received. Thereafter, a set of other reports for which respective second structures of entities are identified is received. A weighting for other reports in the set of other reports is assigned, based on the respective structures. A payment for the existing report is extracted based on the weighting, a selected scoring rule, and the set of other reports.
摘要翻译：提供了一种用于支付现有报告的方法和装置。在该方法中，接收到识别实体的第一结构的现有报告。此后，接收用于识别实体的各个第二结构的一组其他报告。根据各自的结构，分配其他报告中其他报告的权重。根据加权，选定的评分规则和其他报告集，提取现有报告的付款。

9. 发明授权

US08037043B2 Information retrieval system 有权
标题翻译：信息检索系统
公开(公告)号：US08037043B2
公开(公告)日：2011-10-11
申请号：US12207315
申请日：2008-09-09
申请人： Onno Zoeter , Michael J. Taylor , Edward Lloyd Snelson , John P. Guiver , Nicholas Craswell , Martin Szummer
发明人： Onno Zoeter , Michael J. Taylor , Edward Lloyd Snelson , John P. Guiver , Nicholas Craswell , Martin Szummer
IPC分类号： G06F17/30
CPC分类号： G06F17/30675 , G06F17/30864
摘要： An information retrieval system is described for retrieving a list of documents such as web pages or other items from a document index in response to a user query. In an embodiment a prediction engine is used to predict both explicit relevance information such as judgment labels and implicit relevance information such as click data. In an embodiment the predicted relevance information is applied to a stored utility function that describes user satisfaction with a search session. This produces utility scores for proposed lists of documents. Using the utility scores one of the lists of documents is selected. In this way different sources of relevance information are combined into a single information retrieval system in a principled and effective manner which gives improved performance.
摘要翻译：描述了用于响应于用户查询从文档索引检索诸如网页或其他项目的文档列表的信息检索系统。在一个实施例中，预测引擎用于预测诸如判断标签的显式相关性信息和诸如点击数据的隐含相关性信息。在一个实施例中，预测的相关性信息被应用于描述用户对搜索会话的满意度的存储效用函数。这将为拟议的文件清单产生效用分数。使用实用程序得分选择文档列表之一。以这种方式，不同的相关信息来源以原则和有效的方式组合成单个信息检索系统，从而提高了性能。

10. 发明申请

US20100076949A1 Information Retrieval System 有权
标题翻译：信息检索系统
公开(公告)号：US20100076949A1
公开(公告)日：2010-03-25
申请号：US12207315
申请日：2008-09-09
申请人： Onno Zoeter , Michael J. Taylor , Edward Lloyd Snelson , John P. Guiver , Nicholas Craswell , Martin Szummer
发明人： Onno Zoeter , Michael J. Taylor , Edward Lloyd Snelson , John P. Guiver , Nicholas Craswell , Martin Szummer
IPC分类号： G06F7/06 , G06F17/30
CPC分类号： G06F17/30675 , G06F17/30864
摘要： An information retrieval system is described for retrieving a list of documents such as web pages or other items from a document index in response to a user query. In an embodiment a prediction engine is used to predict both explicit relevance information such as judgment labels and implicit relevance information such as click data. In an embodiment the predicted relevance information is applied to a stored utility function that describes user satisfaction with a search session. This produces utility scores for proposed lists of documents. Using the utility scores one of the lists of documents is selected. In this way different sources of relevance information are combined into a single information retrieval system in a principled and effective manner which gives improved performance.
摘要翻译：描述了用于响应于用户查询从文档索引检索诸如网页或其他项目的文档列表的信息检索系统。在一个实施例中，预测引擎用于预测诸如判断标签的显式相关性信息和诸如点击数据的隐含相关性信息。在一个实施例中，预测的相关性信息被应用于描述用户对搜索会话的满意度的存储效用函数。这将为拟议的文件清单产生效用分数。使用实用程序得分选择文档列表之一。以这种方式，不同的相关信息来源以原则和有效的方式组合成单个信息检索系统，从而提高了性能。

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