116 research outputs found

    Unifying Online and Counterfactual Learning to Rank

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    Optimizing ranking systems based on user interactions is a well-studied problem. State-of-the-art methods for optimizing ranking systems based on user interactions are divided into online approaches - that learn by directly interacting with users - and counterfactual approaches - that learn from historical interactions. Existing online methods are hindered without online interventions and thus should not be applied counterfactually. Conversely, counterfactual methods cannot directly benefit from online interventions. We propose a novel intervention-aware estimator for both counterfactual and online Learning to Rank (LTR). With the introduction of the intervention-aware estimator, we aim to bridge the online/counterfactual LTR division as it is shown to be highly effective in both online and counterfactual scenarios. The estimator corrects for the effect of position bias, trust bias, and item-selection bias by using corrections based on the behavior of the logging policy and on online interventions: changes to the logging policy made during the gathering of click data. Our experimental results, conducted in a semi-synthetic experimental setup, show that, unlike existing counterfactual LTR methods, the intervention-aware estimator can greatly benefit from online interventions.Comment: Harrie Oosterhuis and Maarten de Rijke. 2021. Unifying Online and Counterfactual Learning to Rank: A Novel Counterfactual Estimator that Effectively Utilizes Online Interventions. In The 14th ACM International Conference on Web Search and Data Mining (WSDM '21), March 8-12, 2021, Jerusalem, Israel. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3437963.344179

    Scan-line Subdivision Approach to Perspective Texture Mapping

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    Merging static and dynamic visual media along an event timeline

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    Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1998.Includes bibliographical references (p. 63-65).Kyratso Karahalios.M.S

    Appearance-based image splitting for HDR display systems

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    High dynamic range displays that incorporate two optically-coupled image planes have recently been developed. This dual image plane design requires that a given HDR input image be split into two complementary standard dynamic range components that drive the coupled systems, therefore there existing image splitting issue. In this research, two types of HDR display systems (hardcopy and softcopy HDR display) are constructed to facilitate the study of HDR image splitting algorithm for building HDR displays. A new HDR image splitting algorithm which incorporates iCAM06 image appearance model is proposed, seeking to create displayed HDR images that can provide better image quality. The new algorithm has potential to improve image details perception, colorfulness and better gamut utilization. Finally, the performance of the new iCAM06-based HDR image splitting algorithm is evaluated and compared with widely spread luminance square root algorithm through psychophysical studies

    Design and evaluation of multimedia extensions for the DLX architecture

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    Multimedia computer architecture extensions for Hennessy and Patterson\u27s DLX architecture are developed following the study of multimedia applications and existing multimedia architecture extensions. Support for the extensions is added to a VHDL superscalar DLX CPU model as well as a DLX assembler. Key functions used in digital video encoding and decoding are modified to use the extensions, and simulations are undertaken using the VHDL model to determine the speedup offered by the extensions for these functions. The results of the simulations are used to calculate the application speedup based on the function speedup and the fraction of the time that each application spends executing each function. It is shown that the superscalar CPU design limits the performance gain offered by the extensions, and concluded that the effectiveness of the extensions is further limited by the fraction of the application code that can make use of them

    Interactive Video Game Content Authoring using Procedural Methods

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    This thesis explores avenues for improving the quality and detail of game graphics, in the context of constraints that are common to most game development studios. The research begins by identifying two dominant constraints; limitations in the capacity of target gaming hardware/platforms, and processes that hinder the productivity of game art/content creation. From these constraints, themes were derived which directed the research‟s focus. These include the use of algorithmic or „procedural‟ methods in the creation of graphics content for games, and the use of an „interactive‟ content creation strategy, to better facilitate artist production workflow. Interactive workflow represents an emerging paradigm shift in content creation processes used by the industry, which directly integrates game rendering technology into the content authoring process. The primary motivation for this is to provide „high frequency‟ visual feedback that enables artists to see games content in context, during the authoring process. By merging these themes, this research develops a production strategy that takes advantage of „high frequency feedback‟ in an interactive workflow, to directly expose procedural methods to artists‟, for use in the content creation process. Procedural methods have a characteristically small „memory footprint‟ and are capable of generating massive volumes of data. Their small „size to data volume‟ ratio makes them particularly well suited for use in game rendering situations, where capacity constraints are an issue. In addition, an interactive authoring environment is well suited to the task of setting parameters for procedural methods, reducing a major barrier to their acceptance by artists. An interactive content authoring environment was developed during this research. Two algorithms were designed and implemented. These algorithms provide artists‟ with abstract mechanisms which accelerate common game content development processes; namely object placement in game environments, and the delivery of variation between similar game objects. In keeping with the theme of this research, the core functionality of these algorithms is delivered via procedural methods. Through this, production overhead that is associated with these content development processes is essentially offloaded from artists onto the processing capability of modern gaming hardware. This research shows how procedurally based content authoring algorithms not only harmonize with the issues of hardware capacity constraints, but also make the authoring of larger and more detailed volumes of games content more feasible in the game production process. Algorithms and ideas developed during this research demonstrate the use of procedurally based, interactive content creation, towards improving detail and complexity in the graphics of games

    Realtime ray tracing on current CPU architectures

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    In computer graphics, ray tracing has become a powerful tool for generating realistically looking images. Even though ray tracing offers high flexibility, a logarithmic scalability in scene complexity, and is known to be efficiently parallelizable, its demand for compute power has in the past lead to its limitation to high-quality off-line rendering. This thesis focuses on the question of how realtime ray tracing can be realized on current processor architectures. To this end, it provides a detailed analysis of the weaknesses and strengths of current processor architectures, for the purpose of allowing for highly optimized implementation. The combination of processor-specific optimizations with algorithms that exploit the coherence of ray tracing, makes it possible to achieve realtime performance on a single CPU. Besides the optimization of the ray tracing algorithm itself, this thesis focuses on the efficient building of spatial index structures. By building these structures from scratch for every frame, interactive ray tracing of fully dynamic scenes becomes possible. Moreover, a parallelization framework for ray tracing is discussed that efficiently exploits the compute power of a cluster of commodity PCs. Finally, a global illumination algorithm is proposed that efficiently combines optimized ray tracing and the parallelization framework. The combination makes it possible to compute complete global illumination at interactive frame rates

    Image feature analysis using the Multiresolution Fourier Transform

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    The problem of identifying boundary contours or line structures is widely recognised as an important component in many applications of image analysis and computer vision. Typical solutions to the problem employ some form of edge detection followed by line following or, more commonly in recent years, Hough transforms. Because of the processing requirements of such methods and to try to improve the robustness of the algorithms, a number of authors have explored the use of multiresolution approaches to the problem. Non-parametric, iterative approaches such as relaxation labelling and "Snakes" have also been used. This thesis presents a boundary detection algorithm based on a multiresolution image representation, the Multiresolution Fourier Transform (MFT), which represents an image over a range of spatial/spatial-frequency resolutions. A quadtree based image model is described in which each leaf is a region which can be modelled using one of a set of feature classes. Consideration is given to using linear and circular arc features for this modelling, and frequency domain models are developed for them. A general model based decision process is presented and shown to be applicable to detecting local image features, selecting the most appropriate scale for modelling each region of the image and linking the local features into the region boundary structures of the image. The use of a consistent inference process for all of the subtasks used in the boundary detection represents a significant improvement over the adhoc assemblies of estimation and detection that have been common in previous work. Although the process is applied using a restricted set of local features, the framework presented allows for expansion of the number of boundary feature models and the possible inclusion of models of region properties. Results are presented demonstrating the effective application of these procedures to a number of synthetic and natural images

    14th SC@RUG 2017 proceedings 2016-2017

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    14th SC@RUG 2017 proceedings 2016-2017

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