IBM Proposes Effective ML Drift Detection Via Weak Data Slices
An IBM research team leverages weak data slices to propose an effective method for drift detection in machine learning.
Tag: data science
MIT Proposes Novel End-to-End Procedure for Corrupted Data Cleaning, Estimation, and Inference
A research team from MIT proposes a unified framework for estimation and inference in the presence of various forms of economic data corruption such as measurement errors, missing values, discretization, and differential privacy.
Facebook AI & Mila Propose ALMA: Anytime Learning at Macroscale
A research team from Facebook AI Research and Mila – McGill University explores deep learning model accuracy versus time trade-offs in anytime learning, which they term Anytime Learning at Macroscale (ALMA). The team evaluates various models to gain insights on how to strike different trade-offs between accuracy and time to obtain a good learner.
UmlsBERT: Clinical Domain Knowledge Augmentation of Contextual Embeddings Using the Unified Medical Language System Metathesaurus
UmlsBERT is a deep Transformer network architecture that incorporates clinical domain knowledge from a clinical Metathesaurus in order to build ‘semantically enriched’ contextual representations that will benefit from both the contextual learning and domain knowledge.
‘Papers-With-Video’ Browser Extension Adds Video Access to arXiv
A Nepalese machine learning (ML) researcher has introduced a handy browser extension that lets users directly access videos related to research papers published on the popular preprint platform arXiv.
German Startup’s “AI Expert Roadmap” Gets 3.5k GitHub Stars
A new AI Expert Roadmap developed by German software company AMAI is garnering keen interest from aspiring AI professionals around the world.
KDD 2020 Announces Special Diversity & Inclusion Track
Talks, panels and papers dedicated to addressing social inequities and improving inclusivity in data science and artificial intelligence
KDD 2020 Honors Career Achievements in Knowledge Discovery and Data Mining
New Prizes Recognize Innovation, Service, Rising Stars and Enduring Research Papers Ahead of the 26th Annual Conference.
Fujitsu Develops World’s First AI technology to Accurately Capture Characteristics of High-Dimensional Data Without Labeled Training Data
Fujitsu has developed the world’s first AI technology that accurately captures the characteristics of high-dimensional data without labeled training data.
KDD 2020 Opens Registration for 26th Annual Conference With Fully Virtual Program
ACM SIGKDD Will Tap Cutting-Edge Technology to Bring Together the Leading Voices in Knowledge Discovery and Data Mining
SIGKDD Community Impact Program Opens Call for Proposals
SIGKDD is announcing a funding opportunity through its Community Impact Program.
KDD 2020 Opens Call for Research and Applied Data Science Paper Submissions
ACM SIGKDD Invites Industry and Academic Experts to Submit Advancements in Data Mining, Knowledge Discovery and Machine Learning for 26th Annual Conference in San Diego
Masters Will Share Insights at First Toronto Kaggle Days Meetup
Synced would like to invite Toronto AI and data science students and researchers to join representatives of the world’s largest data science community for an evening of networking, discussions, and refreshments!
KDD 2019 Announces Best Paper Awards
KDD 2019 features both a Research track and an Applied Data Science (ADS) track, and today organizers announced their Best Paper Awards.
MIT Is Opening a $1Bn AI College
The Massachusetts Institute of Technology (MIT) today announced they will invest US$1 billion into a new college for artificial intelligence. The MIT Stephen A. Schwarzman College of Computing will “constitute both a global center for computing research and education, and an intellectual foundry for powerful new AI tools.”
UK & France Partner on AI
The Alan Turing Institute in the UK and France’s DATAIA Institute have concluded an arrangement to collaborate in the arena of artificial intelligence and data science, part of a five-year commitment between the two countries to improve digital services.
Applying Data Science to Robotics
In his blog post “How Data Science Apply to Robotics” on Data Science Central, Dr. Ammar A. Raja points out that there are two major problems scientists have encountered while applying data science to robotics.