Abstract: Systems and methods for the automated fulfillment of orders from a fulfillment network including consumer-facing retail locations. Orders are partitioned into suborders, which are in turn assigned to retail locations based on forecasted demand for the suborder items at the retail locations. The assignment process considers operational data for each retail location such as the number of employees, the inventory of suborder items, shipping rate cards, return policies, business hours, pick decline estimations, etc.

Abstract: Systems and methods for the automated fulfillment of orders from a fulfillment network including consumer-facing retail locations. Orders are partitioned into suborders, which are in turn assigned to retail locations based on forecasted demand for the suborder items at the retail locations. The assignment process considers operational data for each retail location such as the number of employees, the inventory of suborder items, shipping rate cards, return policies, business hours, pick decline estimations, etc.

Abstract: Methods and systems for event prediction. The system includes at least one connector configured to gather at least partially incomplete data from at least one data source. The gathered data may be communicated to a model definition module that converts at least a subset of the gathered data into a prediction model in accordance with a received definition. A prediction module may receive a prediction query and, in response, supply an event prediction based on the prediction model.

Abstract: A system includes at least one connector configured to gather at least partially incomplete data from at least one data source. The gathered data is communicated to a model definition module that converts at least a subset of the gathered data into a prediction model in accordance with a received definition. A prediction module receives a prediction query and, in response, supplies an event prediction based on the prediction model.

Abstract: Systems and methods for the automated fulfillment of orders from a fulfillment network including consumer-facing retail locations. Orders are partitioned into suborders, which are in turn assigned to retail locations based on forecasted demand for the suborder items at the retail locations. The assignment process considers operational data for each retail location such as the number of employees, the inventory of suborder items, shipping rate cards, return policies, business hours, pick decline estimations, etc.

Abstract: Systems and methods for the automated fulfillment of orders from a fulfillment network including consumer-facing retail locations. Orders are partitioned into suborders, which are in turn assigned to retail locations based on forecasted demand for the suborder items at the retail locations. The assignment process considers operational data for each retail location such as the number of employees, the inventory of suborder items, shipping rate cards, return policies, business hours, pick decline estimations, etc.

Abstract: Systems and methods for the automated fulfillment of orders from a fulfillment network including consumer-facing retail locations. Orders are partitioned into suborders, which are in turn assigned to retail locations based on forecasted demand for the suborder items at the retail locations. The assignment process considers operational data for each retail location such as the number of employees, the inventory of suborder items, shipping rate cards, return policies, business hours, pick decline estimations, etc.

Abstract: Systems and methods for completing at least one entry in a dataset. The systems and methods described herein find a rich set of dense features for each of a plurality of entities, then combine the rich set of dense features with externally provided features to estimate a target value. The systems and methods combine these features using a neural network model in which portions of the input layer are each only connected to a portion of the hidden layer.

Abstract: Methods and systems for event prediction. The system includes at least one connector configured to gather at least partially incomplete data from at least one data source. The gathered data may be communicated to a model definition module that converts at least a subset of the gathered data into a prediction model in accordance with a received definition. A prediction module may receive a prediction query and, in response, supply an event prediction based on the prediction model.

Abstract: Systems and methodologies are described that facilitate enhanced resource scheduling for a wireless communication system. As described herein, packets associated with a common flow that arrive within a predetermined time period following a leading packet associated with the flow can be grouped into respective packet bursts. Subsequently, system bandwidth, transmit power, and/or other communication resources can be scheduled based on an analysis of the respective packet bursts. As provided herein, by analyzing respective packet bursts in lieu of individual packets, computational and resource overhead required for resource scheduling can be significantly reduced. In one example described herein, a resource schedule is determined by selecting one or more flows to be assigned bandwidth from among a plurality of flows based on an analysis of packet bursts respectively associated with the flows.

Abstract: A method selects an optimal route in a cooperative relay network including a set of nodes. For each node in a set of nodes of a cooperative relay network, dynamically varying channel state information is determined. A transmission policy based on the dynamically varying channel state information is selected, in which the transmission policy includes selected nodes forming an optimal route, a transmission mode for each selected node, and a transmission power for each selected node.

Abstract: A method and system for communicating information in a cooperative relay network of wireless nodes. The wireless nodes including a source, a set of relays, and a destination. Channel state information for each channel between a particular relay of the set of relays and the destination is estimated. A subset of the relays is selected based on the channel state information. The channel state information is fed back to the subset of relays. The source node can then broadcasting data packets from the source to the subset of relays, and the subset of relays forward coherently the data packets from the subset of relays to the destination using beamforming based on the channel state information, while adjusting power to minimize a total energy consumption in the network.

Abstract: Systems and methodologies are described that facilitate enhanced resource scheduling for a wireless communication system. As described herein, packets associated with a common flow that arrive within a predetermined time period following a leading packet associated with the flow can be grouped into respective packet bursts. Subsequently, system bandwidth, transmit power, and/or other communication resources can be scheduled based on an analysis of the respective packet bursts. As provided herein, by analyzing respective packet bursts in lieu of individual packets, computational and resource overhead required for resource scheduling can be significantly reduced. In one example described herein, a resource schedule is determined by selecting one or more flows to be assigned bandwidth from among a plurality of flows based on an analysis of packet bursts respectively associated with the flows.

Abstract: A method selects an optimal route in a cooperative relay network including a set of nodes. For each node in a set of nodes of a cooperative relay network, dynamically varying channel state information is determined. A transmission policy based on the dynamically-varying channel state information is selected, in which the transmission policy includes selected nodes forming an optimal route, a transmission mode for each selected node, and a transmission power for each selected node.

Abstract: A method and system for communicating information in a cooperative relay network of wireless nodes. The wireless nodes including a source, a set of relays, and a destination. Channel state information for each channel between a particular relay of the set of relays and the destination is estimated. A subset of the relays is selected based on the channel state information. The channel state information is fed back to the subset of relays. The source node can then broadcasting data packets from the source to the subset of relays, and the subset of relays forward coherently the data packets from the subset of relays to the destination using beamforming based on the channel state information, while adjusting power to minimize a total energy consumption in the network.