Abstract: A computer-implemented bidding method, computer equipment and a storage medium are provided. The computer-implemented bidding method includes: training a CatBoost regression model through a historical bidding data set, where the historical bidding data set includes bidding configuration parameters as an input of the model and a difference between a first quote and a final quote as an output of the model; and inputting current basic bidding parameters into the trained CatBoost regression model, and outputting values of optimized bidding configuration parameters to configure bidding rules for bidding participants. The computer-implemented bidding method can help a purchaser to purchase a required product at a relatively low price, thereby saving the purchase cost.

Abstract: Systems, methods, and apparatuses can detect whether an impairment is present within a service provider network. The impairment can cause a service provided by the service provider network to not perform as expected. These systems, methods, and apparatuses can develop multiple network records to record the performance of the service provider network at various instances in time. These systems, methods, and apparatuses can compare these network records among each other to detect for the presence of the impairment within the service provider network. These systems, methods, and apparatuses can thereafter diagnose and/or remedy the impairment when present within the service provider network.

Abstract: Authentication based secure federated learning can be beneficial when updates to an initial artificial neural network (ANN) model generated by edge devices are to be aggregated into a federated ANN model. The updates can be generated by the edge devices after training the initial ANN locally. The edge devices can encrypt the updates using edge device-specific identifiers and transmit the encrypted updates to a server. The server can verify the authenticity of the updates, decrypt the updates, and aggregate the updates into the federated ANN model. The aggregation can be performed according to a secure multiparty computation protocol.

Abstract: An apparatus and method for providing high throughput memory responses are provided. The apparatus includes a memory device including a plurality of memory arrays, a memory controller configured to control the memory device, the memory controller having a read queue, a write queue, and an address match circuit, and a data output circuit. The memory controller receives a read request, searches the write queue for a write address that matches a read address of the read request, and sends data associated with the write address from the write queue to the data output circuit without accessing the memory device when the write address matches the read address, the write address that matches the read address being a target address. The data output circuit outputs the data associated with the target address to an external device.

Abstract: A technique for image processing, comprising: receiving input image data, wherein the image data is companded into a first bit depth, wherein the image data includes incomplete color values for pixels of the image data, and wherein the image data is associated with a first color space, interpolating the image data to generate color values for the incomplete color values for pixels of the image data, expanding the image data from the first bit depth to a second bit depth, wherein the color values of the expanded image data have a linear dynamic range, and wherein the second bit depth is higher than the first bit depth, converting the color values for pixels of the expanded image data from the first color space to a second color space, and compressing the color values for pixels of the image data to a third bit depth, the third bit depth lower than the second bit depth, and wherein the compressed color values have a nonlinear dynamic range.

Abstract: Example embodiments relate to enhanced depth of focus cameras using variable apertures and pixel binning. An example embodiment includes a device. The device includes an image sensor. The image sensor includes an array of light-sensitive pixels and a readout circuit. The device also includes a variable aperture. Additionally, the device includes a controller that is configured to cause: the variable aperture to adjust to a first aperture size when a high-light condition is present, the variable aperture to adjust to a second aperture size when a low-light condition is present, the readout circuit to perform a first level of pixel binning when the high-light condition is present, and the readout circuit to perform a second level of pixel binning when the low-light condition is present. The second aperture size is larger than the first aperture size. The second level of pixel binning is greater than the first level of pixel binning.

Abstract: A method is disclosed. The method includes receiving, by a user device, an encrypted message from a server computer. The encrypted message is a message encrypted with a master secret key or a key derived from the master secret key. The user device signs the encrypted message with a secure element private key. The user device, using a whitebox, cryptographically recovers a secure element public key from a certified key using a server computer public key. The certified key is certified by the server computer and based on at least the secure element public key. The user device, using the whitebox, cryptographically recovers the encrypted message from the signed encrypted message using the secure element public key. The user device, using the whitebox, decrypts the encrypted message using the master secret key or the key derived from the master secret key in the whitebox to obtain the message.

Abstract: Local automatic white balance (AWB) of wide dynamic range (WDR) images is provided. Methods and systems include collecting, by an image signal processor (ISP), statistics for local AWB from at least one wide dynamic range (WDR) image received by the ISP; generating, by a processor, based on the statistics, local gain lookup tables (LUTs), one for each color channel represented in the WDR image(s), each local gain LUT providing a correlation between gain and intensity; and storing the local gain LUTs. Further processing includes, for each of multiple pixels of a WDR image to be output calculating an intensity value, accessing the local gain LUT for the color channel corresponding to that pixel using the calculated intensity value to identify a corresponding local gain value, and applying the local gain value to that pixel.

Abstract: Various embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to accurately and concisely generate one or more action item logs of one or more document data objects. For example, certain embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to generate an action item log of a document data object comprising one or more semantically complete or incomplete units of text data, by generating content segmentation units, determining action item presence predictions, generating action item sets from each content segmentation unit within a candidate action item subset, aggregating the action item sets to create an action item log, and storing the action item log.

Abstract: The present disclosure includes apparatuses, methods, and systems for displaying output data from a driver attention model on a display. In an example, an apparatus can include a sensor, an augmented reality (AR) windshield, a memory, and a processor coupled to the memory, the sensor, and the AR windshield, wherein the processor is configured to receive an initial driver attention model, train the initial driver attention model to create a trained driver attention model, transmit the trained driver attention model, receive a global driver attention model based in part on the trained driver attention model, receive sensor data based on operation of the apparatus, run the global driver attention model on the sensor data to generate output data, and cause the output data to be displayed on the AR windshield.

Abstract: Aspects of the disclosure relate to dynamic model configuration and execution. A computing platform may receive first model data comprising first model execution configuration data and first model output configuration data. The computing platform may generate a first model based on the first model execution configuration data. The computing platform may distribute, to a plurality of computing platforms, the first model, the first model execution configuration data, and the first model output configuration data. The computing platform may receive a second request to execute one or more models from a third computing platform. The computing platform may receive, from the third computing platform, first model execution data. The computing platform may execute the first model based on the first model execution data and the first model execution configuration data to generate a first model output score.

Abstract: A computing platform configurable to allow users to graphically represent relationships between database records may be provided to a plurality of organizations. A request to generate a customizable visualization for graphically representing relationships between a root database record and child database records in a customizable format may be processed. Graphical representations of the root database record and the child database records may be caused to be displayed in accordance with the customizable format.

Abstract: Techniques are described herein for concurrent voice assistants. A method includes: providing first and second automated assistants with access to one or more microphones; receiving, from the first automated assistant, an indication that the first automated assistant has initiated a first session, and in response: continuing providing, to the first automated assistant, access to the one or more microphones; discontinuing providing, to the second automated assistant, access to the one or more microphones; and preventing the second automated assistant from accessing one or more portions of an output audio data stream; receiving, from the first automated assistant, an indication that the first session has ended, and in response: continuing providing, to the first automated assistant, access to the one or more microphones; resuming providing, to the second automated assistant, access to the one or more microphones; and resuming providing, to the second automated assistant, the output audio data stream.

Abstract: Apparatuses and methods related to port arbitration of a memory system are described. A memory system can receive a first number of transactions and a second transaction from a first traffic stream and a third number of transactions and a fourth transaction from a second traffic stream. The memory system can process the first number of transactions at least partially concurrently with the third number of transactions. Responsive to a total quantity of transactions of the first number of transactions and the second transaction being at least a threshold quantity of transactions, the second transaction can be processed by the memory system and, subsequent to processing the second transaction, the fourth transaction can be processed by the memory system.

Abstract: System and method are disclosed for training a generative adversarial network pipeline that can produce realistic artificial depth images useful as training data for deep learning networks used for robotic tasks. A generator network receives a random noise vector and a computer aided design (CAD) generated depth image and generates an artificial depth image. A discriminator network receives either the artificial depth image or a real depth image in alternation, and outputs a predicted label indicating a discriminator decision as to whether the input is the real depth image or the artificial depth image. Training of the generator network is performed in tandem with the discriminator network as a generative adversarial network. A generator network cost function minimizes correctly predicted labels, and a discriminator cost function maximizes correctly predicted labels.

Abstract: Techniques for image processing including receiving input image data, wherein the input image data includes data associated with a clear color channel, receiving a color offset value associated with a color channel, wherein color values for the color channel are not provided in the input image data, based on the color offset value, generating intermediate estimated color values for the color channel, wherein generating the intermediate estimated color values includes: clipping color values that have a magnitude greater than the color offset value, and adjusting color values that have a magnitude less than the color offset value based on the color offset value, applying a color correction function to the intermediate estimated color values based on the color offset value to determine color corrected estimated color values, and outputting the color corrected estimated color values.

Abstract: In one aspect, an example method includes (i) identifying, by a playback device, a media device that provides media content to the playback device; (ii) providing, by the playback device, replacement media content for display; (iii) determining, by the playback device, that while the playback device is displaying the replacement media content a remote control transmitted an instruction to the identified media device; (iv) determining, by the playback device, a playback-modification action corresponding to the instruction and the identified media device; and (v) modifying, by the playback device, playback of the replacement media content in accordance with the playback-modification action.

Abstract: A computer implemented method includes receiving input from a first collaborator user device to modify a cell in a collaborative spreadsheet being shared with other collaborators and viewable on other collaborator user devices, sending modifications via a real time channel to the other user devices for display of mirror modifications to the cell prior to commitment of the modifications, and providing an identifier of the first collaborative user device for display of a notice that the first user device is associated with the mirror modifications.

Abstract: Disclosed are systems and methods that provide a framework for machine-assisted discovery of Chondroitinase ABC (ChABC) complexes towards sustained neural regeneration. In some embodiments, the framework may leverage a determination of a diverse set of tailor-made random copolymers that complex and stabilize ChABC at physiological temperature. The copolymer designs, which are based on chain length and/or composition of the copolymers, may be identified using an active machine learning paradigm, which involves, but is not limited to, copolymer synthesis, testing for ChABC thermostability upon copolymer complexation, Gaussian Process Regression modeling and Bayesian optimization. Copolymers are synthesized by automated PET-RAFT, and thermostability of ChABC may be assessed by retained enzyme activity (REA) after a predefined interval of hours at 37° C.

Abstract: In some implementations, the techniques described herein relate to a method including: (i) identifying, by a processor, electronic files stored in association with a user account, (ii) analyzing, by a large language model (LLM) executed by the processor, the electronic files and identifying, based on the LLM analysis, at least one file that is a candidate for deletion, (iii) compiling, by the processor, an electronic message comprising an output indicating deletion of the at least one file, (iv) causing display, by the processor, the electronic message, (v) receiving, by the processor, user input related to the at least one file, (vi) analyzing, by the LLM executed by the processor, the user input, and (vii) performing, by the processor based on the analysis of the user input via the LLM, an action on the at least one file conforming to the user input.