Abstract: An online reservation system is configured to receive requests from a guest for searching property listings and to return property listings that satisfy the search criteria of the requests. The online reservation system uses a machine learning system to rank the property listings returned by the search. The machine learning system uses objective functions to determine parameters for each property listing and assign a ranking based on the parameters. A first objective function generates a parameter indicating an extent to which a property listing matches preferences of the guest, and is based on data about the guest's interactions with the reservation system. A second objective function generates another parameter indicating an extent to which the search request matches the preferences of the host associate with the property listing, and is based on data about the host's responses to reservation requests.

Abstract: Systems and methods are provided for search result optimization using machine learning models. A search system uses machine learning models generate a target vector based on query features of a search query and a set of listing vectors based on listing features of listings identified as part of the search query. The target vector represents an estimated optimal listing for the search query and each listing vector represents a corresponding listing identified as part of the search query. The search system determines distances (e.g., Euclidian distance) between each listing vector and the target vector. The determined distances indicate how similar each listing is to the estimated optimal listing for the search query. The search system ranks the listings based on the distances such that listings that are similar to the estimated optimal listing are ranked higher than listing that are not similar to the estimated optimal listing.

Abstract: A position debiased search system can avoid bias towards top-ranked search results using a position-trained machine-trained model. Past positions for listings can be input into the model with added noise and low-ranked results to train the model to generate rankings that do not exhibit position bias. A network site can implement the position debiased search system to generate network site results that can generate accurate user results in real time as users browse the network site.

Abstract: Systems and methods are provided for search result optimization using machine learning models. A search system uses machine learning models generate a target vector based on query features of a search query and a set of listing vectors based on listing features of listings identified as part of the search query. The target vector represents an estimated optimal listing for the search query and each listing vector represents a corresponding listing identified as part of the search query. The search system determines distances (e.g., Euclidian distance) between each listing vector and the target vector. The determined distances indicate how similar each listing is to the estimated optimal listing for the search query. The search system ranks the listings based on the distances such that listings that are similar to the estimated optimal listing are ranked higher than listing that are not similar to the estimated optimal listing.

Abstract: Systems and methods are provided for search result optimization using machine learning models. A search system uses machine learning models generate a target vector based on query features of a search query and a set of listing vectors based on listing features of listings identified as part of the search query. The target vector represents an estimated optimal listing for the search query and each listing vector represents a corresponding listing identified as part of the search query. The search system determines distances (e.g., Euclidian distance) between each listing vector and the target vector. The determined distances indicate how similar each listing is to the estimated optimal listing for the search query. The search system ranks the listings based on the distances such that listings that are similar to the estimated optimal listing are ranked higher than listing that are not similar to the estimated optimal listing.

Abstract: A position debiased search system can avoid bias towards top-ranked search results using a position-trained machine-trained model. Past positions for listings can be input into the model with added noise and low-ranked results to train the model to generate rankings that do not exhibit position bias. A network site can implement the position debiased search system to generate network site results that can generate accurate user results in real time as users browse the network site.

Abstract: Systems and methods are provided for search result optimization using machine learning models. A search system uses machine learning models generate a target vector based on query features of a search query and a set of listing vectors based on listing features of listings identified as part of the search query. The target vector represents an estimated optimal listing for the search query and each listing vector represents a corresponding listing identified as part of the search query. The search system determines distances (e.g., Euclidian distance) between each listing vector and the target vector. The determined distances indicate how similar each listing is to the estimated optimal listing for the search query. The search system ranks the listings based on the distances such that listings that are similar to the estimated optimal listing are ranked higher than listing that are not similar to the estimated optimal listing.

Abstract: The present invention relates to compositions and methods comprising a retinoic acid receptor inhibitor, a retinoic X receptor inhibitor or an inhibitor of an enzyme in the retinoic acid biosynthesis pathway for treatment of a patient having a solid tumor. In some embodiments, the solid tumor is a sarcoma.

Abstract: A system, method and computer program product are provided for conditionally eliminating a memory read request. In use, a memory read request is identified. Additionally, it is determined whether the memory read request is an unnecessary memory read request. Further, the memory read request is conditionally eliminated, based on the determination.

Abstract: An online reservation system is configured to receive requests from a guest for searching property listings and to return property listings that satisfy the search criteria of the requests. The online reservation system uses a machine learning system to rank the property listings returned by the search. The machine learning system uses objective functions to determine parameters for each property listing and assign a ranking based on the parameters. A first objective function generates a parameter indicating an extent to which a property listing matches preferences of the guest, and is based on data about the guest's interactions with the reservation system. A second objective function generates another parameter indicating an extent to which the search request matches the preferences of the host associate with the property listing, and is based on data about the host's responses to reservation requests.

Abstract: A system, method and computer program product are provided for conditionally eliminating a memory read request. In use, a memory read request is identified. Additionally, it is determined whether the memory read request is an unnecessary memory read request. Further, the memory read request is conditionally eliminated, based on the determination.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for augmenting an interactive session with images. In one aspect, a method includes generating a first linear arrangement of images captured during an interactive session. The images of the first linear arrangement of images can be arranged in order based on a sequence in which the images were captured. The first linear arrangement of images is provided for display. Selection data specifying a selection of an image of the first linear arrangement of images are received. In response to receiving the selection data, a branch point is created at the selected image. The branch point can define a branch from the selected image to a second linear arrangement of images. Additional images captured during the interactive session are received. The second linear arrangement of images is generated that includes the additional images.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for augmenting an interactive session with images. In one aspect, a method includes generating a first linear arrangement of images captured during an interactive session. The images of the first linear arrangement of images can be arranged in order based on a sequence in which the images were captured. The first linear arrangement of images is provided for display. Selection data specifying a selection of an image of the first linear arrangement of images are received. In response to receiving the selection data, a branch point is created at the selected image. The branch point can define a branch from the selected image to a second linear arrangement of images. Additional images captured during the interactive session are received. The second linear arrangement of images is generated that includes the additional images.

Abstract: An integrated circuit design system, method, and computer program product are provided that takes into account signal stability. In use, at least one condition is identified where an output of a logic element before receipt of a clock signal is the same as the output of the logic element after receipt of the clock signal. To this end, such logic element may be disabled based on the identified condition for power savings or other purposes.

Abstract: Synovial sarcoma is an aggressive soft-tissue malignancy. Disclosed herein is an animal model of synovial sarcoma wherein one or more myogenic cells of the animal express recombinant SYT-SSX fusion polypeptide. Using this model, myoblasts were identified as a source of synovial sarcoma. Remarkably, within the skeletal muscle lineage, while expression of the oncoprotein in immature myoblasts leads to induction of synovial sarcoma with 100% penetrance, its expression in more differentiated cells induces myopathy without tumor induction. In addition, early widespread expression of the disclosed fusion protein disrupts normal embryogenesis, causing lethality.

Abstract: An integrated circuit design system, method, and computer program product are provided that takes into account observability based clock gating conditions. In use, at least one condition is identified where an output of a first logic element is not a function of a first input of the first logic element, due to a second input of the first logic element. To this end, at least one second logic element may be disabled based on the identified condition for power savings or other purposes.

Abstract: Electronic design automation tool specifies an architecture at a system level and its component (which include intellectual property (IP) cores like embedded processors, arithmetic logic units (ALU), multipliers, dividers, embedded memory element, programmable logic cells, etc.); specifies IP-cores and their interface; and understands IP-cores and functions via their interface. Further, techniques are provided for modeling the timing behavior of a function or functional block without drawing a timing diagram; understanding the interface behavior of a function block which captures the timing waveforms; specifying virtual functions which are built using basic functional units and their timing behavior; parsing and creating an internal graphical form for analyzing a specification for compilation; matching the components in the architecture specification and their instantiation to map the computations in the input graph produced from an application; and mapping the specification onto the target's components.

Abstract: A system, method and computer program product are provided for generating and manipulating a compressed data structure. Initially, a plurality of values associated with an ordered collection of bits is received. It is then determined which of the values are the same. To this end, a compressed data structure including the values is generated, based on the determination.

Abstract: Digital circuit is synthesized from algorithm described in the MATLAB programming language. A MATLAB program is compiled into RTL-VHDL, which is synthesizable using system-specific tools to develop ASIC or FPGA configuration. Intermediate transformations and optimizations are performed to obtain highly optimized description in RTL-VHDL or RTL Verilog of given MATLAB program. Optimizations include levelization, scalarization, pipelining, type-shape analysis, memory optimizations, precision analysis and scheduling.

Abstract: Digital circuit is synthesized from algorithm described in the MATLAB programming language. A MATLAB program is compiled into RTL-VHDL, which is synthesizable using system-specific tools to develop ASIC or FPGA configuration. Intermediate transformations and optimizations are performed to obtain highly optimized description in RTL-VHDL or RTL Verilog of given MATLAB program. Optimizations include levelization, scalarization, pipelining, type-shape analysis, memory optimizations, precision analysis and scheduling.