Posts by «arcarter»

Name:
arcarter

A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU and Sparse, Heterogeneous Clinical Data

by: in: Research

We evaluate the use of multivariate timeseries modeling with the multi-task Gaussian process (GP) models using noisy, incomplete, sparse, heterogeneous and unevenlysampled clinical data, including both physiological signals and clinical notes. The learned multi-task GP (MTGP) hyperparameters are then used to assess and forecast patient acuity. Presenter: Tristan Naumann Paper: ghassemi_AAAI2015_multivariate_timeseries_modeling Poster: MIT_AAAI_MTGP_lg

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A Scalable Architecture for Ordered Parallelism

by: in: Research

Swarm: a novel architecture that exploits ordered irregular parallelism, which is abundant but hard to mine with current software and hardware techniques. In this architecture, programs consist of short tasks with programmer-specified timestamps. Swarm executes tasks speculatively and out of order, and efficiently speculates thousands of tasks ahead of the earliest active task to uncover […]

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Dynamic Generation and Prefetching of Data Tiles for Exploratory Visualization

by: in: Research

ForeCache: a general-purpose tool for exploratory browsing of large datasets. ForeCache utilizes a clientserver architecture, where the user interacts with a lightweight clientside interface to browse datasets, and the data to be browsed is retrieved from a DBMS running on a back-end server. Presenter: Leilani Battle Poster: forecache_small Paper: MIT-CSAIL-TR-2015-031

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BlueDBM: An Appliance for Big Data Analytics

by: in: Research

BlueDBM: a new system architecture which has flash- based storage with in-store processing capability and a low- latency high-throughput inter-controller network. BlueDBM presents an attractive point in the cost-performance trade-off for Big Data analytics. Paper: ISCA15_Sang-Woo_Jun Presenter: Sang-Woo Jun Poster: poster

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Making Sense of Big Data Using Question Answering

by: in: Research

Question answering can help us make sense of Big Data by reducing a massive collection of documents into a relevant answer. Knowledge bases constructed automatically from the Web are rich sources of answers, but they suffer from sparsity in the relations that connect entities. For example, we can express that a person studied at a […]

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Decibel: Versioning for the DataHub Platform

by: in: Research

Decibel: A data management systems that natively support the versioning or branching of datasets to enable concurrent analysis, cleaning, integration, manipulation, or curation of data across teams of individuals. Presenter: David Goehring Paper: Decibel: The Relational Dataset Branching System Poster: Decibel Poster Slides: Decibel Presentation

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Nested Vector Language: Machine-level Performance for Data Parallel Code

by: in: Research

NVL is a simple and expressive intermediate language for data parallel computations that targets vector units, multicores, GPUs, and other high-performance features of modern machines, allowing developers of data parallel applications to achieve excellent performance without extensive development effort. NVL’s simplicity enables powerful program analysis and aggressive optimization. When different NVL-enabled libraries are composed by […]

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