Results 81 to 90 of about 477 (109)

Statistical-Computational Trade-offs for Density Estimation

Neural Information Processing Systems
We study the density estimation problem defined as follows: given $k$ distributions $p_1, \ldots, p_k$ over a discrete domain $[n]$, as well as a collection of samples chosen from a ``query'' distribution $q$ over $[n]$, output $p_i$ that is ``close'' to
Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Sandeep Silwal, Haike Xu   +6 more
semanticscholar   +1 more source

Learning-Augmented Frequent Directions

International Conference on Learning Representations
An influential paper of Hsu et al. (ICLR'19) introduced the study of learning-augmented streaming algorithms in the context of frequency estimation. A fundamental problem in the streaming literature, the goal of frequency estimation is to approximate the
Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu   +4 more
semanticscholar   +1 more source

Snakes in the Plane: Controllable Gliders in a Nanomagnetic Metamaterial

arXiv.org
The magnetic metamaterials known as Artificial Spin Ice (ASI) are promising candidates for neuromorphic computing, composed of vast numbers of interacting nanomagnets arranged in the plane.
Arthur Penty, Johannes H. Jensen, Ida Breivik, Anders Strømberg, E. Folven, Gunnar Tufte   +5 more
semanticscholar   +1 more source

GPTreeO: An R package for continual regression with dividing local Gaussian processes

arXiv.org
We introduce GPTreeO, a flexible R package for scalable Gaussian process (GP) regression, particularly tailored to continual learning problems. GPTreeO builds upon the Dividing Local Gaussian Processes (DLGP) algorithm, in which a binary tree of local GP
Timo Braun, Anders Kvellestad, Riccardo De Bin   +2 more
semanticscholar   +1 more source

A fast 2D-AR(1) filtering for bitemporal change detection on UWB SAR images

Environmental Remote Sensing
This article presents an elementary change detection algorithm designed using a synchronous model of computation (MoC) aiming at efficient implementations on parallel architectures. The change detection method is based on a 2D-first-order autoregressive (
Marcello G. Costa, Ingo Sander, I. Söderquist, Patrik Dammert, Anders Åhlander, Christer Fuglesang   +5 more
semanticscholar   +1 more source

Of Concurrent Data Structures and Iterations

Algorithms, Probability, Networks, and Games, 2015
Y. Nikolakopoulos, Anders Gidenstam, M. Papatriantafilou, P. Tsigas   +3 more
semanticscholar   +1 more source

Lightweight semiformal time complexity analysis for purely functional data structures

ACM-SIGACT Symposium on Principles of Programming Languages, 2008
Nils Anders Danielsson
semanticscholar   +1 more source

MRI‐PET Registration with Automated Algorithm

Journal of computer assisted tomography, 1993
R. Woods, J. Mazziotta, and Simon R. Cherry   +2 more
semanticscholar   +1 more source

Noisy intermediate-scale quantum algorithms

Reviews of Modern Physics, 2022
Kishor Bharti, Alba Cervera-lierta, Thi Ha Kyaw   +2 more
exaly  

Discovering faster matrix multiplication algorithms with reinforcement learning

Nature, 2022
Alhussein Fawzi, Mohammadamin Barekatain, David Silver   +2 more
exaly