Tweaking tools to track tweets over time
Feb 17, 2019
Computer model learns to identify Twitter users’ evolving interests by analyzing their Tweets.
Results for machine learning
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Causal disentanglement is the next frontier in AI
Feb 19, 2019
Recreating the human mind’s ability to infer patterns and relationships from complex events could lead to a universal model of artificial intelligence.
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Accelerating the grapevine effect
Jul 3, 2019
Gossip is an efficient way to share information across large networks and has unexpected applications in solving other mathematical and machine-learning problems.
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A breath of fresh information to help diagnosis
Aug 4, 2019
A communications concept could pinpoint a person infected with a deadly, contagious virus in the middle of a crowded airport.
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Testing the blind spots in artificial intelligence
Aug 29, 2019
Understanding the situations when artificial intelligence can fail is critical for application of future autonomous vehicles and medical diagnostics.
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Database to support infectious disease research
Sep 11, 2019
Linking disease pathogens to clinical signs and symptoms through a database could support research into the molecular mechanisms of infectious diseases.
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Speeding up the machine learning process
Sep 26, 2019
A new approach for training algorithms makes the machine learning process faster and more accurate.
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Less chat leads to more work for machine learning
Oct 15, 2019
Deep analysis of the way information is shared among parallel computations increases efficiency to accelerate machine learning at scale.
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Machine learning models gather momentum
Nov 24, 2019
New methods for training machine learning models are quicker and more accurate than current approaches, previously considered state-of-the-art.
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LD Motif Finder locates ancient hidden protein patterns
Jan 6, 2020
A machine learning method has identified highly elusive amino acid sequences involved in cell morphogenesis and adhesion and in diseases like cancer.
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AI uses your imagination
Jan 14, 2020
The psychology of human creativity helps artificial intelligence imagine the unseen.
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Approximating a kernel of truth
Mar 10, 2020
Machine learning tasks using very large data sets can be sped up significantly by estimating the kernel function that best describes the data.
