Yahoo! Inc.

Hangzhou Fabu Technology Co., Ltd.

Xiaofei He

Hang T Nguyen

Yu Cao

Pradhuman Jhala

Jeffrey Hao Chu

Wei Vivian Zhang

Bahaa Osman

Abinash Mohanty

Siddartha Kavilipati

Yong Xiao

Provided are a method and an apparatus for debugging, and a system on chip. The method for debugging includes: a component to be debugged receives a debugging instruction from a controller, and the component to be debugged performs debugging operation according to the debugging instruction and configuration of a state machine inside the component to be debugged. Then an SW level debugging operation of component on system on chip can be achieved, which improves the debugging efficiency of these components with large amounts of data flow on system on chip.

Method and apparatus for debugging, and system on chip

Provided are a scalable data fusion method and related products. The scalable data fusion method is applied in a central device and includes: receiving sensing data transmitted by each of M first edge devices, wherein M is an integer equal to or greater than 1; fusing the sensing data transmitted by each of the M first edge devices to obtain M pieces of fused data respectively corresponding to the M first edge devices; distributing the M pieces of fused data to the M first edge devices respectively; receiving object information transmitted by each of the M first edge devices, wherein the object information is obtained based on the fused data; and integrating the object information transmitted by each of the M first edge devices and construct surrounding information based on the integrated object information.

Scalable data fusion architecture and related products

The present disclosure provides a method for checking a to-be-checked signal and related products. The method is applied in a checking device and includes: a first obtaining module, configured to obtain a to-be-checked signal carrying first control information, wherein the first control information is generated based on original control information; a second obtaining module, configured to obtain original checking information; a determining module, configured to determine the first control information according to the to-be-checked signal; and a checking module, configured to check correctness of the first control information according to the original checking information. The present disclosure can be used to enable reliability and functional safety on devices originally designed without features intended to support those functions.

Method for checking address and control signal integrity in functional safety applications, related products

Provided are a proposals processing method and related products for object detection, where the method comprising: determining a score threshold according to a statistics property of scores of a first quantity of proposal; selecting a second quantity of proposals with a score higher than the score threshold from the first quantity of proposals; and suppressing to the second quantity of proposals to get a third quantity of non-overlapping proposals with high scores, as such, time complexity for selecting a second quantity of proposals is reduced, and efficiency for selection of the proposals to be used for suppression is improved, thereby improving proposal processing efficiency and object detection efficiency.

Proposal processing method and related products

Embodiments of methods, apparatuses, devices and systems associated with one or more representative images are disclosed.

System, method, and apparatus for selecting one or more representative images

Systems and methods for determining semantically related terms using an active learning framework such as Transductive Experimental Design are disclosed. Generally, to enhance a keyword suggestion tool, an active learning module trains a model to predict whether a term is relevant to a user. The model is then used to present the user with terms that have been determined to be relevant based on the model so that an online advertisement service provider may more efficiently provide a user with terms that are semantically related to a seed set.

System and method for determining semantically related terms using an active learning framework

Described are a system and method for selecting a training sample from a sample set. The method comprises determining proximities between all data samples in a set of the data samples, forming edges between the data samples as a function of the proximities, computing weights for the edges as a function of the proximities, selecting a plurality of the data samples as a function of the weights to form a subset of the data samples, and storing the subset of the data samples.

System and method for selecting a training sample from a sample test based on data sample proximity

This disclosure describes systems and methods for categorizing web pages. Web pages and terms selected from those web pages are organized in a matrix. The number of terms in the matrix are filtered using a Laplacian score algorithm. A linear regression algorithm or some other algorithm may use the filtered set of terms to fit the web pages into pre-defined categories.

Web page categorization using graph-based term selection

A system is described for classifying a search query. The system may create a machine learning classifier function that may be 'trained' by a plurality of categorized queries within a query taxonomy. The system may represent the queries as term vectors and input the term vectors to the machine learning classifier function to generate a value that may correspond to a particular category within the query taxonomy. The system may regularize the machine learning classifier function based on user search click data to improve the classifying accuracy.

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Hangzhou, China

Xiaofei He