Abstract: A wheeled carrying apparatus includes a frame structure including a standing frame, a wheel mount carrying a wheel and pivotally connected with the standing frame, the wheel being rotatable relative to the first wheel mount about a wheel axis, a locking assembly including a wheel mount latch movably connected with the standing frame, the wheel mount latch being engaged with the wheel mount to rotationally lock the first wheel mount with respect to the standing frame, and disengaged from the wheel mount to unlock the wheel mount for rotation of the wheel mount to change an orientation of the wheel axis, an actuating assembly coupled to the wheel mount latch and including one or more linking part, and a release mechanism including an operating part provided on the frame structure that is operable to cause the actuating assembly to pull the wheel mount latch to disengage from the wheel mount.

Abstract: The present disclosure is directed toward systems, methods, and computer readable media for training and utilizing an item-level importance sampling model to evaluate and execute digital content selection policies. For example, systems described herein include training and utilizing an item-level importance sampling model that accurately and efficiently predicts a performance value that indicates a probability that a target user will interact with ranked lists of digital content items provided in accordance with a target digital content selection policy. Specifically, systems described herein can perform an offline evaluation of a target policy in light of historical user interactions corresponding to a training digital content selection policy to determine item-level importance weights that account for differences in digital content item distributions between the training policy and the target policy.

Abstract: The present disclosure is directed toward systems, methods, and computer readable media for training and utilizing an item-level importance sampling model to evaluate and execute digital content selection policies. For example, systems described herein include training and utilizing an item-level importance sampling model that accurately and efficiently predicts a performance value that indicates a probability that a target user will interact with ranked lists of digital content items provided in accordance with a target digital content selection policy. Specifically, systems described herein can perform an offline evaluation of a target policy in light of historical user interactions corresponding to a training digital content selection policy to determine item-level importance weights that account for differences in digital content item distributions between the training policy and the target policy.

Abstract: Systems and techniques for multi-task equidistant embedding are described that process categorical feature data to explore feature interactions. A digital analytics system enforces an equidistant relationship among features within a category while extracting high-order feature interactions by punishing both positive correlations and negative correlations among low-dimensional representations of different features. By enforcing an equidistant embedding, information is retained and accuracy is increased while higher order feature interactions are determined. Further, the digital analytics system shares knowledge among different tasks by connecting a shared network representation common to multiple tasks with exclusive network representations specific to particular tasks.

Abstract: Disclosed herein is a content-adaptive digital media content adjustment system, method and architecture. Playback rate of a media content item comprising audio and video content can be increased by removing a portion of the content item's audio content and a corresponding portion of the content item's video content. An increased playback rate of a multimedia content item is accomplished by decreasing the length of the multimedia content item by removing portions of the multimedia content item's audio and video content.

Abstract: Recommendation systems and techniques are described that employ change point detection to generate recommendations for digital content. In one example, a change point detection technique is employed by a recommendation system to identify when a change point has occurred at a respective time step of a series of time steps. Detection of this change point may then be used by the recommendation system to reset the statistical model to address this change as well as generate a subsequent recommendation configured for exploration of reward distributions of the items of digital marketing content.

Abstract: Systems and methods for customizing an interactive experience based on topics determined from an online topic model. In an example, a segmentation application executing on a computing device accesses past user interaction vectors that represent interaction data from an electronic content delivery system. The segmentation application accesses a segmentation model having parameters. The segmentation application updates the parameters by performing tensor decomposition on a tensor built from the past user interaction vectors and calculating updating values of the parameters from the tensor decomposition. The segmentation application performs a segmentation of user devices by applying the segmentation model with the updated parameters to the present user interaction vector. The segmentation assigns the user device to the user segment. The segmentation application transmits data describing the segmentation to the electronic content delivery system.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for determining parameters for digital campaign content in connection with executing digital campaigns using a rank-one assumption and a best-arm identification algorithm. For example, the disclosed system alternately explores response data in the first dimension and response data in the second dimension using the rank-one assumption and the best-arm identification algorithm to estimate highest sampling values from each dimension. In one or more embodiments, the disclosed system uses the estimated highest sampling values from the first and second dimension to determine a combination with a highest sampling value in a parameter matrix constructed based on the first dimension and the second dimension, and then executes the digital campaign using the determined combination.

Abstract: The present disclosure is directed toward systems, methods, and computer readable media for training and utilizing an item-level importance sampling model to evaluate and execute digital content selection policies. For example, systems described herein include training and utilizing an item-level importance sampling model that accurately and efficiently predicts a performance value that indicates a probability that a target user will interact with ranked lists of digital content items provided in accordance with a target digital content selection policy. Specifically, systems described herein can perform an offline evaluation of a target policy in light of historical user interactions corresponding to a training digital content selection policy to determine item-level importance weights that account for differences in digital content item distributions between the training policy and the target policy.

Abstract: A machine-learning framework uses partial-click feedback to generate an optimal diverse set of items. An example method includes estimating a preference vector for a user based on diverse cascade statistics for the user, the diverse cascade statistics including previously observed responses and previously observed topic gains. The method also includes generating an ordered set of items from the item repository, the items in the ordered set having highest topic gain weighted by similarity with the preference vector, providing the ordered set for presentation to the user, and receiving feedback from the user on the ordered set. The method also includes, responsive to the feedback indicating a selected item, updating the diverse cascade statistics for observed items, wherein the updating results in penalizing the topic gain for items of the observed items that are not the selected item and promoting the topic gain for the selected item.

Abstract: An infant stroller apparatus includes a front leg frame, a rear leg frame and a handle frame. The front leg frame has a first side portion fixedly connected with a first stop abutment. The rear leg frame has a second side portion having a protrusion. The handle frame has a side segment fixedly connected with a second stop abutment, the first and second side portions and the side segment being pivotally connected with one another about a common first pivot axis. The protrusion is restrictedly positioned between the first and second stop abutments when the infant stroller apparatus is in a deployed state.

Abstract: Disclosed is a method for wireless typology discovery for train backbone networks.

Abstract: Influence maximization determination within a social network system is described. In one example, a subset is selected from a plurality of user accounts of a social network system. Exposure of digital marketing content is then caused to the subset of user accounts. A determination is made as to a probability of each user account of the plurality of user accounts as being influenced by the exposure of the digital marketing content to the subset of user accounts. The determined probability is then output, such as to control output of digital marketing content.

Abstract: Disclosed herein is a content-adaptive digital media content adjustment system, method and architecture. Playback rate of a media content item comprising audio and video content can be increased by removing a portion of the content item's audio content and a corresponding portion of the content item's video content. An increased playback rate of a multimedia content item is accomplished by decreasing the length of the multimedia content item by removing portions of the multimedia content item's audio and video content.

Abstract: Disclosed herein is a content-adaptive digital media content adjustment system, method and architecture. Playback rate of a media content item comprising audio and video content can be increased by removing a portion of the content item's audio content and a corresponding portion of the content item's video content. An increased playback rate of a multimedia content item is accomplished by decreasing the length of the multimedia content item by removing portions of the multimedia content item's audio and video content.

Abstract: An infant stroller apparatus includes a front leg frame, a rear leg frame and a handle frame. The front leg frame has a first side portion fixedly connected with a first stop abutment. The rear leg frame has a second side portion having a protrusion. The handle frame has a side segment fixedly connected with a second stop abutment, the first and second side portions and the side segment being pivotally connected with one another about a common first pivot axis. The protrusion is restrictedly positioned between the first and second stop abutments when the infant stroller apparatus is in a deployed state.

Abstract: An infant stroller apparatus includes a front and a rear leg frame respectively having a first and a second side portion, a handle frame having a side segment, a seat frame and a bar linkage. The first and second side portions and the side segment are pivotally connected with one another about a first pivot axis. The seat frame is pivotally connected with the side segment about a second pivot axis. The bar linkage has a first and a second end respectively connected pivotally with the second side portion and the seat frame about a third and a fourth pivot axis. When the infant stroller apparatus is deployed, the second pivot axis is above the first pivot axis, the third pivot axis is above the first pivot axis, and the fourth pivot axis is above and behind the first pivot axis.

Abstract: Disclosed is a method for wireless typology discovery for train backbone networks.

Abstract: Disclosed herein is a content-adaptive digital media content adjustment system, method and architecture. Playback rate of a media content item comprising audio and video content can be increased by removing a portion of the content item's audio content and a corresponding portion of the content item's video content. An increased playback rate of a multimedia content item is accomplished by decreasing the length of the multimedia content item by removing portions of the multimedia content item's audio and video content.

Abstract: An infant stroller apparatus includes a front and a rear leg frame respectively having a first and a second side portion, a handle frame having a side segment, a seat frame and a bar linkage. The first and second side portions and the side segment are pivotally connected with one another about a first pivot axis. The seat frame is pivotally connected with the side segment about a second pivot axis. The bar linkage has a first and a second end respectively connected pivotally with the second side portion and the seat frame about a third and a fourth pivot axis. When the infant stroller apparatus is deployed, the second pivot axis is above the first pivot axis, the third pivot axis is above the first pivot axis, and the fourth pivot axis is above and behind the first pivot axis.