Publications associées à On Multidimensional Data and Modern Disks

Dimensionality reduction of time-series data, and systems and devices that use the resultant embeddings

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for dimensionality reduction of time-series using contrastive learning. A method can include receiving multidimensional input time series data that includes ...

2023

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Sachin Basil John

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

EPFL2023

Aggregation and Exploration of High-Dimensional Data Using the Sudokube Data Cube Engine

Christoph Koch, Sachin Basil John, Peter Lindner, Zhekai Jiang

We present Sudokube, a novel system that supports interactive speed querying on high-dimensional data using partially materialized data cubes. Given a storage budget, it judiciously chooses what projections to precompute and materialize during cube constru ...

Association for Computing Machinery2023

A reduced-order, rotation-based model for thin hard-magnetic plates

Pedro Miguel Nunes Pereira de Almeida Reis, Dong Yan, Bastien Freddy Gustave Aymon

We develop a reduced-order model for thin plates made of hard magnetorheological elastomers (hard-MREs), which are composed of hard-magnetic particles embedded in a polymeric matrix. First, we propose a new magnetic potential, as an alternative to an exist ...

PERGAMON-ELSEVIER SCIENCE LTD2023

HPCache: Memory-Efficient OLAP Through Proportional Caching

Anastasia Ailamaki, Periklis Chrysogelos, Hamish Mcniece Hill Nicholson

Analytical engines rely on in-memory caching to avoid disk accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- & time-based caching decisions, however, are a proxy of the expected query execution ...

ACM2022

Manifold Learning-Based Polynomial Chaos Expansions For High-Dimensional Surrogate Models

Ketson Roberto Maximiano Dos Santos

In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantitie ...

2022

Information-driven transitions in projections of underdamped dynamics

Amos Maritan, Daniel Maria Busiello, Giorgio Nicoletti

Low-dimensional representations of underdamped systems often provide useful insights and analytical tractability. Here, we build such representations via information projections, obtaining an optimal model that captures the most information on observed spa ...

AMER PHYSICAL SOC2022

Beating the I/O Bottleneck: A Case for Log-Structured Virtual Disks

Vojtech Aschenbrenner

With the increasing dominance of SSDs for local storage, today's network mounted virtual disks can no longer offer competitive performance. We propose a Log-Structured Virtual Disk (LSVD) that couples log-structured approaches at both the cache and storage ...

ASSOC COMPUTING MACHINERY2022

Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data

Matthieu Wyart, Umberto Maria Tomasini, Antonio Sclocchi

Recently, several theories including the replica method made predictions for the generalization error of Kernel Ridge Regression. In some regimes, they predict that the method has a 'spectral bias': decomposing the true function f* on the eigenbasis of the ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

Synthesis of branching morphologies

Henry Markram, Lida Kanari

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for generating model neurons. In one aspect, a method includes receiving a plurality of descriptions of branches of dendrites of one or more neurons and gener ...

2021

Micro-architectural analysis of in-memory OLTP: Revisited

Anastasia Ailamaki, Danica Porobic, Utku Sirin

Micro-architectural behavior of traditional disk-based online transaction processing (OLTP) systems has been investigated extensively over the past couple of decades. Results show that traditional OLTP systems mostly under-utilize the available micro-archi ...

2021

MOSES: A Streaming Algorithm for Linear Dimensionality Reduction

Armin Eftekhari

This paper introduces Memory-limited Online Subspace Estimation Scheme (MOSES) for both estimating the principal components of streaming data and reducing its dimension. More specifically, in various applications such as sensor networks, the data vectors a ...

IEEE COMPUTER SOC2020

Exploring the Extent in the Visual Field of the Honeycomb and Extinction Illusions

Michael Herzog, Aline Françoise Cretenoud

There are situations in which what is perceived in central vision is different to what is perceived in the periphery, even though the stimulus display is uniform. Here, we studied two cases, known as the Extinction illusion and the Honeycomb illusion, invo ...

2019

Large-Eddy Simulation of Yawed Wind-Turbine Wakes: Comparisons with Wind Tunnel Measurements and Analytical Wake Models

Fernando Porté Agel, Mou Lin

In this study, we validated a wind-turbine parameterisation for large-eddy simulation (LES) of yawed wind-turbine wakes. The presented parameterisation is modified from the rotational actuator disk model (ADMR), which takes account of both thrust and tange ...

2019

Fourier dimensionality reduction for fast radio transients

Jean-Philippe Thiran, Yves Wiaux, Vijay Kartik, Ming Jiang

In the context of next-generation radio interferometers, we are facing a big challenge of how to economically process data. The classical dimensionality reduction technique, averaging visibilities on time, may dilute fast radio transients (FRT). We propose ...

2019

Time- and Space-Efficient Spatial Data Analytics

Mirjana Pavlovic

Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...

EPFL2019

On Force Synergies in Human Grasping Behavior

Aude Billard, Konstantinos Chatzilygeroudis

The human hand is a versatile and complex system with dexterous manipulation capabilities. For the transfer of human grasping capabilities to humanoid robotic and prosthetic hands, an understanding of the dynamic characteristics of grasp motions is fundame ...

IEEE2019

Reconstruction and simulation of neocortical microcircuitry

Henry Markram, Felix Schürmann, Sean Lewis Hill, Eilif Benjamin Muller

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for reconstructing and simulating neocortical microcircuitry. In one aspect, a method includes providing a model of neural tissue, the model including differ ...

2018

Overcoming the time-bandwidth limit

Camille Sophie Brès, Davide Grassani, Simon Julien Fabbri, Ivan Cardea, Kosmas Tsakmakidis

We are so accustomed to the time-bandwidth limit that we often take it to be a fundamental relation that cannot be overcome. Contrary to this belief we here propose that the storage/delay time of a system can in fact be decoupled from the operating bandwid ...

IEEE2018

BLOCK: Efficient Execution of Spatial Range Queries in Main-Memory

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Matthaios Alexandros Olma

The execution of spatial range queries is at the core of many applications, particularly in the simulation sciences but also in many other domains. Although main memory in desktop and supercomputers alike has grown considerably in recent years, most spatia ...

ACM New York, NY, USA2017