TL;DR: System R as mentioned in this paper is an experimental database management system developed to carry out research on the relational model of data, which chooses access paths for both simple (single relation) and complex queries (such as joins), given a user specification of desired data as a boolean expression of predicates.
Abstract: In a high level query and data manipulation language such as SQL, requests are stated non-procedurally, without reference to access paths. This paper describes how System R chooses access paths for both simple (single relation) and complex queries (such as joins), given a user specification of desired data as a boolean expression of predicates. System R is an experimental database management system developed to carry out research on the relational model of data. System R was designed and built by members of the IBM San Jose Research Laboratory.
TL;DR: It is observed that despite their hierarchical convolutional nature, the synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unhealthy manner, and small architectural changes are derived that guarantee that unwanted information cannot leak into the hierarchical synthesis process.
Abstract: We observe that despite their hierarchical convolutional nature, the synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unhealthy manner. This manifests itself as, e.g., detail appearing to be glued to image coordinates instead of the surfaces of depicted objects. We trace the root cause to careless signal processing that causes aliasing in the generator network. Interpreting all signals in the network as continuous, we derive generally applicable, small architectural changes that guarantee that unwanted information cannot leak into the hierarchical synthesis process. The resulting networks match the FID of StyleGAN2 but differ dramatically in their internal representations, and they are fully equivariant to translation and rotation even at subpixel scales. Our results pave the way for generative models better suited for video and animation.
TL;DR: The results suggest that contrary to most expectations, with some modifications, a native implementations in an RDBMS can support this class of query much more efficiently.
Abstract: Virtually all proposals for querying XML include a class of query we term “containment queries”. It is also clear that in the foreseeable future, a substantial amount of XML data will be stored in relational database systems. This raises the question of how to support these containment queries. The inverted list technology that underlies much of Information Retrieval is well-suited to these queries, but should we implement this technology (a) in a separate loosely-coupled IR engine, or (b) using the native tables and query execution machinery of the RDBMS? With option (b), more than twenty years of work on RDBMS query optimization, query execution, scalability, and concurrency control and recovery immediately extend to the queries and structures that implement these new operations. But all this will be irrelevant if the performance of option (b) lags that of (a) by too much. In this paper, we explore some performance implications of both options using native implementations in two commercial relational database systems and in a special purpose inverted list engine. Our performance study shows that while RDBMSs are generally poorly suited for such queries, under conditions they can outperform an inverted list engine. Our analysis further identifies two significant causes that differentiate the performance of the IR and RDBMS implementations: the join algorithms employed and the hardware cache utilization. Our results suggest that contrary to most expectations, with some modifications, a native implementations in an RDBMS can support this class of query much more efficiently.
TL;DR: The main design goals of the new system are toprovide better support for complex objects, provide user extendibility for data types, operators and access methods, provide facilities for active databases and inferencing including forward- and backward-chaining.
Abstract: This paper presents the preliminary design of a new database management system, called POSTGRES, that is the successor to the INGRES relational database system. The main design goals of the new system are to provide better support for complex objects,provide user extendibility for data types, operators and access methods,provide facilities for active databases (i.e., alerters and triggers) and inferencing including forward- and backward-chaining,simplify the DBMS code for crash recovery,produce a design that can take advantage of optical disks, workstations composed of multiple tightly-coupled processors, and custom designed VLSI chips, andmake as few changes as possible (preferably none) to the relational model.The paper describes the query language, programming language interface, system architecture, query processing strategy, and storage system for the new system.
TL;DR: Ownership types form a static type system that indicates object ownership, which provides a flexible mechanism to limit the visibility of object references and restrict access paths to objects, thus controlling a system's dynamic topology.
Abstract: Object-oriented programming languages allow inter-object aliasing. Although necessary to construct linked data structures and networks of interacting objects, aliasing is problematic in that an aggregate object's state can change via an alias to one of its components, without the aggregate being aware of any aliasing.Ownership types form a static type system that indicates object ownership. This provides a flexible mechanism to limit the visibility of object references and restrict access paths to objects, thus controlling a system's dynamic topology. The type system is shown to be sound, and the specific aliasing properties that a system's object graph satisfies are formulated and proven invariant for well-typed programs.