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Designing scalable estimation algorithms is a core challenge in modern statistics. Here we introduce a framework to address this challenge based on parallel approximants, which yields estimators with provable properties that operate on the…

Methodology · Statistics 2023-08-04 Aritra Chakravorty , William S. Cleveland , Patrick J. Wolfe

Business success of companies heavily depends on the availability and performance of their client applications. Due to modern development paradigms such as DevOps and microservice architectural styles, applications are decoupled into…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-10 Sina Niedermaier , Falko Koetter , Andreas Freymann , Stefan Wagner

The persistent programming systems of the 1980s offered a programming model that integrated computation and long-term storage. In these systems, reliable applications could be engineered without requiring the programmer to write translation…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-06-21 Alan Dearle , Graham Kirby , Stuart Norcross , Andrew McCarthy

The ability to detect objects in images at varying scales has played a pivotal role in the design of modern object detectors. Despite considerable progress in removing hand-crafted components and simplifying the architecture with…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Duy-Kien Nguyen , Martin R. Oswald , Cees G. M. Snoek

Existing weakly-supervised semantic segmentation methods using image-level annotations typically rely on initial responses to locate object regions. However, such response maps generated by the classification network usually focus on…

Computer Vision and Pattern Recognition · Computer Science 2020-08-05 Yu-Ting Chang , Qiaosong Wang , Wei-Chih Hung , Robinson Piramuthu , Yi-Hsuan Tsai , Ming-Hsuan Yang

Object detection and instance recognition play a central role in many AI applications like autonomous driving, video surveillance and medical image analysis. However, training object detection models on large scale datasets remains…

Computer Vision and Pattern Recognition · Computer Science 2019-03-15 Yuntao Chen , Chenxia Han , Yanghao Li , Zehao Huang , Yi Jiang , Naiyan Wang , Zhaoxiang Zhang

Segmenting object parts such as cup handles and animal bodies is important in many real-world applications but requires more annotation effort. The largest dataset nowadays contains merely two hundred object categories, implying the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-29 Tai-Yu Pan , Qing Liu , Wei-Lun Chao , Brian Price

Most distributed storage systems provide limited abilities for querying data by attributes other than their primary keys. Supporting efficient search on secondary attributes is challenging as applications pose varying requirements to query…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-03-13 Dimitrios Vasilas , Marc Shapiro , Bradley King

When programming resource-scarce embedded smart devices, the designer often requires both the low-level system programming features of a language such as C and higher level capability typical of a language like Java. The choice of a…

Programming Languages · Computer Science 2019-10-09 Vincenzo De Florio , Chris Blondia

We propose a new method to count objects of specific categories that are significantly smaller than the ground sampling distance of a satellite image. This task is hard due to the cluttered nature of scenes where different object categories…

Computer Vision and Pattern Recognition · Computer Science 2018-09-21 Andres C. Rodriguez , Jan D. Wegner

A flexible, scalable and affordable virtual reality software system architecture is proposed. This solution can be easily implemented on different hardware configurations: on a single computer or on a computer cluster. The architecture is…

Graphics · Computer Science 2013-08-28 Stoyan Maleshkov , Dimo Chotrov

In this paper, we present distributed generalized clustering algorithms that can handle large scale data across multiple machines in spite of straggling or unreliable machines. We propose a novel data assignment scheme that enables us to…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-17 Venkata Gandikota , Arya Mazumdar , Ankit Singh Rawat

A system, which implements persistent objects, has to provide different opportunities to change the objects in arbitrary ways during their existence. A traditional realization of OO paradigm in modern programming systems has fundamental…

Programming Languages · Computer Science 2013-04-12 Evgeniy Grigoriev

Data mining algorithms are originally designed by assuming the data is available at one centralized site.These algorithms also assume that the whole data is fit into main memory while running the algorithm. But in today's scenario the data…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-03 Aruna Govada , Bhavul Gauri , S. K. Sahay

Design by Contract enables seamless software development by unifying software requirements with their implementations. In its pure form, however, Design by Contract leaves some problems with contracts' expressiveness, verifiability, and…

Software Engineering · Computer Science 2019-11-26 Alexandr Naumchev

In this paper, we study the problem of generating structured objects that conform to a complex schema, with intricate dependencies between the different components (facets) of the object. The facets of the object (attributes, fields,…

Software Engineering · Computer Science 2024-12-02 Amir Tavanaei , Kee Kiat Koo , Hayreddin Ceker , Shaobai Jiang , Qi Li , Julien Han , Karim Bouyarmane

Consensus is an often occurring problem in concurrent and distributed programming. We present a programming language with simple semantics and build-in support for consensus in the form of communicating transactions. We motivate the need…

Programming Languages · Computer Science 2013-05-08 Carlo Spaccasassi , Vasileios Koutavas

Implementing a component-based system in a distributed way so that it ensures some global constraints is a challenging problem. We consider here abstract specifications consisting of a composition of components and a controller given in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-07-30 Imene Ben-Hafaiedh , Susanne Graf , Hammadi Khairallah

Semantic Abstraction's key observation is that 2D VLMs' relevancy activations roughly correspond to their confidence of whether and where an object is in the scene. Thus, relevancy maps are treated as "abstract object" representations. We…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Tasha Pais , Nikhilesh Belulkar

Distributed computing platforms provide a robust mechanism to perform large-scale computations by splitting the task and data among multiple locations, possibly located thousands of miles apart geographically. Although such distribution of…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-24 Alok Singh , Eric Stephan , Malachi Schram , Ilkay Altintas
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