Search Results for author:
Found 14 papers, 5 papers with code
Dynamic Parameter Allocation in Parameter Servers
To keep up with increasing dataset sizes and model complexity, distributed training has become a necessity for large machine learning tasks.
NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access
Parameter servers (PSs) facilitate the implementation of distributed training for large machine learning tasks.
Good Intentions: Adaptive Parameter Management via Intent Signaling
Parameter management is essential for distributed training of large machine learning (ML) tasks.
Missing Value Imputation for Multi-attribute Sensor Data Streams via Message Propagation (Extended Version)
First, we propose a message propagation imputation network (MPIN) that is able to recover the missing values of data instances in a time window.
Sharing Hash Codes for Multiple Purposes
In this paper, we propose {multiple purpose LSH (mp-LSH) which shares the hash codes for different dissimilarities.
BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding
This paper presents the BigEarthNet that is a new large-scale multi-label Sentinel-2 benchmark archive.
A Survey of State Management in Big Data Processing Systems
State management and its use in diverse applications varies widely across big data processing systems.
Databases
Agora: A Unified Asset Ecosystem Going Beyond Marketplaces and Cloud Services
Data, algorithms, and compute/storage infrastructure are key assets that drive data science and artificial intelligence applications.
Benchmarking Distributed Stream Data Processing Systems
Third, we build the first benchmarking framework to define and test the sustainable performance of streaming systems.
Databases ieee.org
BigEarthNet-MM: A Large Scale Multi-Modal Multi-Label Benchmark Archive for Remote Sensing Image Classification and Retrieval
In our experiments, we show the potential of BigEarthNet-MM for multi-modal multi-label image retrieval and classification problems by considering several state-of-the-art DL models.
Towards Loosely-Coupling Knowledge Graph Embeddings and Ontology-based Reasoning
Knowledge graph completion (a. k. a.~link prediction), i. e.,~the task of inferring missing information from knowledge graphs, is a widely used task in many applications, such as product recommendation and question answering.
Satellite Image Search in AgoraEO
To address this limitation, we have recently proposed MiLaN, a content-based image retrieval approach for fast similarity search in satellite image archives.
Artificial intelligence to advance Earth observation: a perspective
Earth observation (EO) is a prime instrument for monitoring land and ocean processes, studying the dynamics at work, and taking the pulse of our planet.
