Database meets artificial intelligence: A survey
Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can
make database more intelligent (AI4DB). For example, traditional empirical database …
make database more intelligent (AI4DB). For example, traditional empirical database …
Cost-based or learning-based? A hybrid query optimizer for query plan selection
Traditional cost-based optimizers are efficient and stable to generate optimal plans for
simple SQL queries, but they may not generate high-quality plans for complicated queries …
simple SQL queries, but they may not generate high-quality plans for complicated queries …
Practices for Managing Machine Learning Products: A Multivocal Literature Review
Machine learning (ML) has grown in popularity in the software industry due to its ability to
solve complex problems. Developing ML systems involves more uncertainty and risk …
solve complex problems. Developing ML systems involves more uncertainty and risk …
Data cleaning and machine learning: a systematic literature review
PO Côté, A Nikanjam, N Ahmed, D Humeniuk… - Automated Software …, 2024 - Springer
Abstract Machine Learning (ML) is integrated into a growing number of systems for various
applications. Because the performance of an ML model is highly dependent on the quality of …
applications. Because the performance of an ML model is highly dependent on the quality of …
Selective data acquisition in the wild for model charging
The lack of sufficient labeled data is a key bottleneck for practitioners in many real-world
supervised machine learning (ML) tasks. In this paper, we study a new problem, namely …
supervised machine learning (ML) tasks. In this paper, we study a new problem, namely …
Feature augmentation with reinforcement learning
Sufficient good features are indispensable to train well-performed machine learning models.
However, it is com-mon that good features are not always enough, where feature …
However, it is com-mon that good features are not always enough, where feature …
Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: A perspective for healthcare organizations
P Esmaeilzadeh - Artificial Intelligence in Medicine, 2024 - Elsevier
Healthcare organizations have realized that Artificial intelligence (AI) can provide a
competitive edge through personalized patient experiences, improved patient outcomes …
competitive edge through personalized patient experiences, improved patient outcomes …
Goodcore: Data-effective and data-efficient machine learning through coreset selection over incomplete data
Given a dataset with incomplete data (eg, missing values), training a machine learning
model over the incomplete data requires two steps. First, it requires a data-effective step that …
model over the incomplete data requires two steps. First, it requires a data-effective step that …
Learned data-aware image representations of line charts for similarity search
Finding line-chart images similar to a given line-chart image query is a common task in data
exploration and image query systems, eg finding similar trends in stock markets or medical …
exploration and image query systems, eg finding similar trends in stock markets or medical …
Learnedsqlgen: Constraint-aware sql generation using reinforcement learning
Many database optimization problems, eg, slow SQL diagnosis, database testing, optimizer
tuning, require a large volume of SQL queries. Due to privacy issues, it is hard to obtain real …
tuning, require a large volume of SQL queries. Due to privacy issues, it is hard to obtain real …