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Tensors are often compressed by expressing them in low rank tensor formats. In this paper, we develop three methodologies that bound the compressibility of a tensor: (1) Algebraic structure, (2) Smoothness, and (3) Displacement structure.…

Numerical Analysis · Mathematics 2020-02-04 Tianyi Shi , Alex Townsend

The paper gives a soundness and completeness proof for the implicative fragment of intuitionistic calculus with respect to the semantics of computability logic, which understands intuitionistic implication as interactive algorithmic…

Logic in Computer Science · Computer Science 2011-04-15 Giorgi Japaridze

This letter presents a novel small gripper capable of grasping various types of small-sized items from flat surfaces for the assembly of small devices. Using a single actuator, the proposed gripper realizes two grasping modes: parallel-grip…

Robotics · Computer Science 2021-06-21 Tetsuyou Watanabe , Kota Morino , Yoshitatsu Asama , Seiji Nishitani , Ryo Toshima

Caging is a promising tool which allows a robot to manipulate an object without directly reasoning about the contact dynamics involved. Furthermore, caging also provides useful guarantees in terms of robustness to uncertainty, and often…

Robotics · Computer Science 2019-08-05 Bernardo Aceituno-Cabezas , Hongkai Dai , Alberto Rodriguez

This document describes a convention for compressing FITS binary tables that is modeled after the FITS tiled-image compression method (White et al. 2009) that has been in use for about a decade. The input table is first optionally…

Instrumentation and Methods for Astrophysics · Physics 2012-01-09 William Pence , Rob Seaman , Richard L. White

The paper introduces a new technique for compressing Binary Decision Diagrams in those cases where random access is not required. Using this technique, compression and decompression can be done in linear time in the size of the BDD and…

Artificial Intelligence · Computer Science 2008-12-18 Esben Rune Hansen , S. Srinivasa Rao , Peter Tiedemann

Long context inference presents challenges at the system level with increased compute and memory requirements, as well as from an accuracy perspective in being able to reason over long contexts. Recently, several methods have been proposed…

Computation and Language · Computer Science 2024-07-15 Siddharth Jha , Lutfi Eren Erdogan , Sehoon Kim , Kurt Keutzer , Amir Gholami

Technological growth in the electronics industry has historically been measured by the number of transistors that can be crammed onto a single microchip. Unfortunately, all good things must come to an end; spectacular growth in the number…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Veronica Cerletti , W. A. Coish , Oliver Gywat , Daniel Loss

Quantum computing not only holds the potential to solve long-standing problems in quantum physics, but also to offer speed-ups across a broad spectrum of other fields. However, due to the noise and the limited scale of current quantum…

Quantum Physics · Physics 2024-03-05 Julien Gacon

We introduce a new formalisation of languages, called keyboards. We consider a set of elementary operations (writing/erasing a letter, going to the right or to the left,...) and we define a keyboard as a set of finite sequences of such…

Formal Languages and Automata Theory · Computer Science 2021-09-07 Yoan Géran , Bastien Laboureix , Corto Mascle , Valentin D. Richard

This study starts from the counter-intuitive question of how we can render a conventional stiff, non-stretchable and even brittle material conformable so that it can fully wrap around a curved surface, such as a sphere, without failure.…

Computational Geometry · Computer Science 2018-12-31 Yu-Ki Lee , Zhonghua Xi , Young-Joo Lee , Yun-Hyeong Kim , Yue Hao , Young-Chang Joo , Changsoon Kim , Jyh-Ming Lien , In-Suk Choi

Transformer-based self-supervised models have achieved remarkable success in speech processing, but their large size and high inference cost present significant challenges for real-world deployment. While numerous compression techniques…

Computation and Language · Computer Science 2025-08-19 Tzu-Quan Lin , Tsung-Huan Yang , Chun-Yao Chang , Kuang-Ming Chen , Tzu-hsun Feng , Hung-yi Lee , Hao Tang

Model compression is generally performed by using quantization, low-rank approximation or pruning, for which various algorithms have been researched in recent years. One fundamental question is: what types of compression work better for a…

Machine Learning · Computer Science 2021-07-12 Miguel Á. Carreira-Perpiñán , Yerlan Idelbayev

A change of the prevalent supervised learning techniques is foreseeable in the near future: from the complex, computational expensive algorithms to more flexible and elementary training ones. The strong revitalization of randomized…

Machine Learning · Computer Science 2022-09-02 Antonello Rosato , Massimo Panella , Evgeny Osipov , Denis Kleyko

Compressed sensing is a novel research area, which was introduced in 2006, and since then has already become a key concept in various areas of applied mathematics, computer science, and electrical engineering. It surprisingly predicts that…

Information Theory · Computer Science 2012-08-29 Gitta Kutyniok

Large neural models are often compressed before deployment. Model compression is necessary for many practical reasons, such as inference latency, memory footprint, and energy consumption. Compressed models are assumed to be miniature…

Machine Learning · Computer Science 2024-07-19 Rohit Raj Rai , Rishant Pal , Amit Awekar

Electromagnetic systems have been used extensively for the control magnetically actuated objects, such as in microrheology and microrobotics research. Therefore, optimizing the design of such systems is highly desired. Some of the features…

Robotics · Computer Science 2022-11-03 Max Sokolich , Max Sokolich , David Rivas , Markos Duey , Daniel Borsykowsky , Sambeeta Das

Physical keyboards are common peripherals for personal computers and are efficient standard text entry devices. Recent research has investigated how physical keyboards can be used in immersive head-mounted display-based Virtual Reality…

Successful adoption of deep learning (DL) in the wild requires models to be: (1) compact, (2) accurate, and (3) robust to distributional shifts. Unfortunately, efforts towards simultaneously meeting these requirements have mostly been…

Machine Learning · Computer Science 2021-11-09 James Diffenderfer , Brian R. Bartoldson , Shreya Chaganti , Jize Zhang , Bhavya Kailkhura

Computer simulations serve as powerful tools for scientists and engineers to gain insights into complex systems. Less costly than physical experiments, computer experiments sometimes involve large number of trials. Conventional design…

Methodology · Statistics 2025-06-06 Xu He , Junpeng Gong , Zhaohui Li
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