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Found 21 papers, 6 papers with code
FLAC: A Robust Failure-Aware Atomic Commit Protocol for Distributed Transactions
Consequently, it improves both the response time and throughput, and effectively handles nodes distributed across the Internet where crash and network failures might occur.
The Metaverse Data Deluge: What Can We Do About It?
In the Metaverse, the physical space and the virtual space co-exist, and interact simultaneously.
Towards Robust Cross-domain Image Understanding with Unsupervised Noise Removal
In multimedia analysis, domain adaptation studies the problem of cross-domain knowledge transfer from a label rich source domain to a label scarce target domain, thus potentially alleviates the annotation requirement for deep learning models.
A Survey on Deep Reinforcement Learning for Data Processing and Analytics
Data processing and analytics are fundamental and pervasive.
SINGA-Easy: An Easy-to-Use Framework for MultiModal Analysis
Specifically, in terms of usability, it is demanding for non-experts to implement deep learning models, obtain the right settings for the entire machine learning pipeline, manage models and datasets, and exploit external data sources all together.
ARM-Net: Adaptive Relation Modeling Network for Structured Data
The key idea is to model feature interactions with cross features selectively and dynamically, by first transforming the input features into exponential space, and then determining the interaction order and interaction weights adaptively for each cross feature.
AlphaEvolve: A Learning Framework to Discover Novel Alphas in Quantitative Investment
In this paper, we introduce a new class of alphas to model scalar, vector, and matrix features which possess the strengths of these two existing classes.
Serverless Data Science -- Are We There Yet? A Case Study of Model Serving
Data scientists today have to manage the end-to-end ML life cycle that includes both model training and model serving, the latter of which is essential, as it makes their works available to end-users.
MLCask: Efficient Management of Component Evolution in Collaborative Data Analytics Pipelines
In this paper, we identify two main challenges that arise during the deployment of machine learning pipelines, and address them with the design of versioning for an end-to-end analytics system MLCask.
A Transactional Perspective on Execute-order-validate Blockchains
For evaluation, we implement our method in two blockchains respectively, FabricSharp on top of Hyperledger Fabric, and FastFabricSharp on top of FastFabric.
Distributed, Parallel, and Cluster Computing Databases Performance
Analysis of Indexing Structures for Immutable Data
We establish the worst-case guarantees of each index in terms of these five metrics, and we experimentally evaluate all indexes in a large variety of settings.
Databases
Blockchains vs. Distributed Databases: Dichotomy and Fusion
As blockchain evolves into another data management system, the natural question is how it compares against distributed database systems.
Databases Performance
The Disruptions of 5G on Data-driven Technologies and Applications
With 5G on the verge of being adopted as the next mobile network, there is a need to analyze its impact on the landscape of computing and data management.
Networking and Internet Architecture Databases Distributed, Parallel, and Cluster Computing
Database Meets Deep Learning: Challenges and Opportunities
Deep learning has recently become very popular on account of its incredible success in many complex data-driven applications, such as image classification and speech recognition.
Effective and Efficient Dropout for Deep Convolutional Neural Networks
However, many recent works show that the standard dropout is ineffective or even detrimental to the training of CNNs.
Object-Level Representation Learning for Few-Shot Image Classification
Few-shot learning that trains image classifiers over few labeled examples per category is a challenging task.
PANDA: Facilitating Usable AI Development
In many complex applications such as healthcare, subject matter experts (e. g. Clinicians) are the ones who appreciate the importance of features that affect health, and their knowledge together with existing knowledge bases are critical to the end results.
Rafiki: Machine Learning as an Analytics Service System
Second, expertise knowledge is required to optimize the training and inference procedures in terms of efficiency and effectiveness, which imposes heavy burden on the system users.
ForkBase: An Efficient Storage Engine for Blockchain and Forkable Applications
By integrating the core application properties into the storage, ForkBase not only delivers high performance but also reduces development effort.
Databases Cryptography and Security Distributed, Parallel, and Cluster Computing
Cross-Domain Image Retrieval with Attention Modeling
For query images, we use each candidate image in the database as the context to locate the query attention.
Untangling Blockchain: A Data Processing View of Blockchain Systems
Blockchain technologies are gaining massive momentum in the last few years.
Databases Cryptography and Security
