Generating large labeled training data is becoming the biggest bottleneck in building and deploying supervised machine learning models. Recently, the data programming paradigm has been proposed to reduce the human cost in labeling training data. Howe...
We study the data-scaling of transfer learning from foundation models in the low-downstream-data regime. We observe an intriguing phenomenon which we call cliff-learning. Cliff-learning refers to regions of data-scaling laws where performance improve...
Copy-Paste has proven to be a very effective data augmentation for instance segmentation which can improve the generalization of the model. We used a task-specific Copy-Paste data augmentation method to achieve good performance on the instance segmen...
You can view a summary of the Google services you use and the data saved in your Google Account. Step 1: View an overview of your data Find Google services you used while signed in to your account.
Manage other location data If you have other settings like Web & App Activity turned on, and you pause Location History or delete location data from Location History, you may still have location data saved …
Reads weather data packets sent by AcuRite Access devices and makes the data accessible locally. Also supports ingesting data from rtl_433 software shared via MQTT. (⭐ 5)
People and machines are collecting data at an unprecedented rate. Despite this newfound abundance of data, progress has been slow in sharing it for open science, business, and other data-intensive endeavors. Many such efforts are stymied by privacy c...
The ADS All-Sky Survey (ADSASS) is an ongoing effort aimed at turning the NASA Astrophysics Data System (ADS), widely known for its unrivaled value as a literature resource for astronomers, into a data resource. The ADS is not a data repository per s...
It is well known that to accelerate stencil codes on CPUs or GPUs and to exploit hardware caches and their lines optimizers must find spatial and temporal locality of array accesses to harvest data-reuse opportunities. On FPGAs there is the burden th...
We propose a new method for representing data sets with a set of binary feature functions. We compute both the dyadic set structure determined by an order on the binary features together with the canonical product coefficient parameters for the assoc...
A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently. (⭐ 3310)
Despite increasing accessibility to function data, effective methods for flexibly estimating underlying functional trend are still scarce. We thereby develop functional version of trend filtering for estimating trend of functional data indexed by tim...
In this paper, we propose a vital data analysis platform which resolves existing problems to utilize vital data for real-time actions. Recently, IoT technologies have been progressed but in the healthcare area, real-time actions based on analyzed vit...
In this paper, we propose a vital data analysis platform which resolves existing problems to utilize vital data for real-time actions. Recently, IoT technologies have been progressed but in the healthcare area, real-time actions based on analyzed vit...
Privacy labels -- standardized, compact representations of data collection and data use practices -- are often presented as a solution to the shortcomings of privacy policies. Apple introduced mandatory privacy labels for apps in its App Store in Dec...
Manage data in your Google Account: Third-party apps or services may request permission to edit, upload, create, or delete data in your Google Account. A film editor app may edit your video and …
Understand your unique viewers data You can use unique viewers data to get a clearer picture of your audience size, or the estimated number of viewers who came to watch your videos over a given time …
Bioinformatics research is characterized by voluminous and incremental datasets and complex data analytics methods. The machine learning methods used in bioinformatics are iterative and parallel. These methods can be scaled to handle big data using t...
Q&A for people interested in statistics, machine learning, data analysis, data mining, and data visualization
Amida is a leader in health informatics and data analytics. Our expertise spans healthcare information systems, data standards, analytic methodologies, and business operations.