Current Algorithms News and Events

Current Algorithms News and Events, Algorithms News Articles.
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Researchers develop speedier network analysis for a range of computer hardware
MIT researchers developed software to more efficiently run graph applications on a range of computing hardware, including both CPUs and GPUs. The advance could boost analysis of social networks, recommendation algorithms, and internet search. (2021-02-22)

Applying quantum computing to a particle process
A team of researchers at Lawrence Berkeley National Laboratory (Berkeley Lab) used a quantum computer to successfully simulate an aspect of particle collisions that is typically neglected in high-energy physics experiments, such as those that occur at CERN's Large Hadron Collider. (2021-02-12)

How shared partisanship leads to social media connections
MIT scholars have found that Twitter users are three times more likely to follow other Twitter accounts they are aligned with in political terms, showing how much partisan identification itself drives social groupings. (2021-02-11)

Brain activity can reveal the severity of autistic traits
A team of researchers from Russia and Israel applied a new algorithm to classify the severity of autistic personality traits by studying subjects' brain activity. The article 'Brief Report: Classification of Autistic Traits According to Brain Activity Recoded by fNIRS Using ε-Complexity Coefficients' is published in the Journal of Autism and Developmental Disorders. (2021-02-11)

A study presents an algorithm that automates electrocardiogram recordings
Artificial intelligence can help health personnel to diagnose heart diseases, as shown in a study published in Scientific Reports, by Guillermo Jiménez-Pérez and Oscar Camara, members of the PhySense group, and Alejandro Alcaine, a researcher at the University of San Jorge, Zaragoza. (2021-02-09)

The Ramanujan Machine
The study, which was published in the journal Nature, was carried out by undergraduates from different faculties under the tutelage of Assistant Professor Ido Kaminer of the Andrew and Erna Viterbi Faculty of Electrical Engineering at the Technion. (2021-02-05)

RUDN University mathematicians reduced neural network size six times without post-training
A team of mathematicians from RUDN University found a way to reduce the size of a trained neural network six times without spending additional resources on re-training it. The approach is based on finding a correlation between the weights of neural connections in the initial system and its simplified version. (2021-02-05)

Toshiba's new algorithms quickly deliver highly accurate solutions to complex problems
Toshiba has announced new algorithms developed from the Simulated Bifurcation algorithm (SB). Innovations that include quasi-quantum tunneling ensure the algorithms far surpass the speed and accuracy of the previous SB, and quickly find solutions to highly complex problems in areas as diverse as drug development, portfolio management and logistics management. Details are published in the Science Advances on February 3. (2021-02-04)

MARLIT, artificial intelligence against marine litter
Floating sea macro-litter is a threat to the conservation of marine ecosystems worldwide. The largest density of floating litter is in the great ocean gyres -systems of circular currents that spin and catch litter- but the polluting waste is abundant in coastal waters and semi closed seas such as the Mediterranean. (2021-02-04)

Smartwatch sensors enable remote monitoring & treatment guidance for Parkinson's patients
Scientists have developed a monitoring system based on commercial smartwatches that can detect movement issues and tremors in patients with Parkinson's disease. (2021-02-03)

Amazon spreads vaccine misinformation, iSchool researchers find
Amazon's search algorithm gives preferential treatment to books that promote false claims about vaccines, according to research by UW Information School Ph.D. student Prerna Juneja and Assistant Professor Tanu Mitra. (2021-02-02)

A full-scale prototype for muon tomography
In this article of EPJ Plus, researchers build on previous studies into detection technologies and reconstruction algorithms for muon tomography, to develop a full-scale muon tomograph prototype. (2021-02-01)

"Liquid" machine-learning system adapts to changing conditions
MIT researchers developed a neural network that learns on the job, not just during training. The ''liquid'' network varies its equations' parameters, enhancing its ability to analyze time series data. The advance could boost autonomous driving, medical diagnosis, and more. (2021-01-28)

Machine-learning to predict the performance of organic solar cells
Researchers from the Universitat Rovira i Virgili (URV) specialized in Artificial Intelligence have collaborated with researchers from Institute of Materials Science of Barcelona, specialized on materials for energy applications, to combine the experimental data points that they gather with artificial intelligence algorithms and enable an unprecedented predicting capability of the performance of organic solar cells. (2021-01-28)

Smart algorithm cleans up images by searching for clues buried in noise
In a new study published in Nature Machine Intelligence, researchers at Texas A&M University have unveiled a machine learning-based algorithm that can reduce graininess in low-resolution images and reveal new details that were otherwise buried within the noise. (2021-01-26)

New advances in the detection of bias in face recognition algorithms
A team from the Computer Vision Center (CVC) and the University of Barcelona has published the results of a study that evaluates the accuracy and bias in gender and skin colour of automatic face recognition algorithms tested with real world data. Although the top solutions exceed the 99.9% of accuracy, researchers have detected some groups that show higher false positive or false negative rates. (2021-01-25)

Merging technologies with color to avoid design failures
Various software packages can be used to evaluate products and predict failure; however, these packages are extremely computationally intensive and take a significant amount of time to produce a solution. Quicker solutions mean less accurate results. (2021-01-20)

Rethinking spin chemistry from a quantum perspective
Summary Researchers at Osaka City University use quantum superposition states and Bayesian inference to create a quantum algorithm, easily executable on quantum computers, that accurately and directly calculates energy differences between the electronic ground and excited spin states of molecular systems in polynomial time. (2021-01-18)

Robot learns fast but safe navigation strategy
A research group from the Active Intelligent System Laboratory (AISL) at Toyohashi University of Technology (TUT) has proposed a new framework for training mobile robots to quickly navigate while maintaining low collision rates. The framework combines deep reinforcement learning (DRL) and curriculum learning in the training process for robots to learn a fast but safe navigation policy. (2021-01-18)

Artificial Intelligence beats us in chess, but not in memory
A new piece of research shows that the brain strategy for storing memories may lead to imperfect memories, but in turn, allows it to store more memories, and with less hassle than AI. The new study, carried out by SISSA scientists in collaboration with Kavli Institute for Systems Neuroscience & Centre for Neural Computation, Trondheim, Norway, has just been published in Physical Review Letters. (2021-01-15)

When AI is used to set prices, can inadvertent collusion be a result?
CATONSVILLE, MD, January 12, 2021 - Machine learning and artificial intelligence (AI) are perfectly suited to help companies and marketers monitor and set prices based on real-time dynamic pricing. But new research has identified some possible unintended consequences of AI in this area. (2021-01-12)

Team creates hybrid chips with processors and memory to run AI on battery-powered devices
Transactions between processors and memory can consume 95 percent of the energy needed to do machine learning and AI, which severely limits battery life. A team led by Stanford engineers has designed a system that can run AI tasks faster, and with less energy, by harnessing eight hybrid chips, each with its own data processor built right next to its own memory storage. (2021-01-11)

Accelerating AI computing to the speed of light
A University of Washington-led team has come up with a system that could help speed up AI performance and find ways to reduce its energy consumption: an optical computing core prototype that uses phase-change material. (2021-01-08)

Light-based processors boost machine-learning processing
An international team of scientists have developed a photonic processor that uses rays of light inside silicon chips to process information much faster than conventional electronic chips. Published in Nature, the breakthrough study was carried out by scientists from EPFL, the Universities of Oxford, Münster, Exeter, Pittsburgh, and IBM Research - Zurich. (2021-01-06)

Story tips: Nanoscale commuting, easy driver and defect detection
ORNL story tips: Nanoscale commuting, easy driver and defect detection. (2021-01-05)

AI algorithms detect diabetic eye disease inconsistently
In a paper published Jan. 5 in Diabetes Care, researchers compared seven algorithms to detect diabetic retinopathy against the diagnostic expertise of retina specialists. (2021-01-05)

DUAL takes AI to the next level
Scientists at DGIST in Korea, and UC Irvine and UC San Diego in the US, have developed a computer architecture that processes unsupervised machine learning algorithms faster, while consuming significantly less energy than state-of-the-art graphics processing units. The key is processing data where it is stored in computer memory and in an all-digital format. The researchers presented the new architecture, called DUAL, at the 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture. (2020-12-30)

Quick look under the skin
Imaging techniques enable a detailed look inside an organism. But interpreting the data is time-consuming and requires a great deal of experience. Artificial neural networks open up new possibilities: They require just seconds to interpret whole-body scans of mice and to segment and depict the organs in colors, instead of in various shades of gray. This facilitates the analysis considerably. (2020-12-28)

NTU Singapore study suggests link between word choices and extraverts
A study by a team of Nanyang Technological University, Singapore (NTU Singapore) psychologists has found a link between extraverts and their word choices. (2020-12-27)

Machine intelligence accelerates research into mapping brains
Scientists in Japan's brain science project have used machine intelligence to improve the accuracy and reliability of a powerful brain-mapping technique, a new study reports. Their development, published on December 18th in Scientific Reports, gives researchers more confidence in using the technique to untangle the human brain's wiring and to better understand the changes in this wiring that accompany neurological or mental disorders such as Parkinson's or Alzheimer's disease. (2020-12-18)

Earable computing: A new research area in the making
Research Group (SyNRG) at UIUC is defining a new sub-area of mobile technology that they call ''earable computing.'' The team believes that earphones will be the next significant milestone in wearable devices, and that new hardware, software, and apps will all run on this platform. (2020-12-15)

Experts advocate responsible and transparent use of algorithms in government
Amsterdam, NL, December 14, 2020 - The use of algorithms in government is transforming the way bureaucrats work and make decisions in different areas, such as healthcare or criminal justice. Experts address the transparency challenges of using algorithms in decision-making procedures at the macro-, meso-, and micro-levels in this special issue of Information Polity. (2020-12-14)

Bristol researchers publish significant step toward quantum advantage
Researchers from the University of Bristol and quantum start-up, Phasecraft, have achieved a milestone in quantum computing research, accelerating the journey from theory to research to reality. (2020-12-10)

Noninvasive way to explore traumatic brain injuries
A noninvasive method to measure the stiffness parameters along fibrous pathways within the brain is helping researchers explore traumatic brain injuries. The stiffness of these tissues can reveal clues about changes and pathologies within the brain's gray and white matter. During the 179th ASA Meeting, Anthony J. Romano will describe the method known as waveguide elastography. Waveguide elastography merges magnetic resonance elastography and diffusion tensor imaging with a combination of isotropic and anisotropic inversion algorithms. (2020-12-09)

Researchers create framework to help determine timing of cancer mutations
UCLA researchers studying cancer evolution have created a framework to help determine which tool combinations are best for pinpointing the exact timing of DNA mutations in cancer genomes. (2020-12-07)

The ever-elusive riddle: What's the best way to cut Christmas cookies?
At some point in life, most people have stood over a rolled-out slab of cookie dough and pondered just how to best cut out cookies with as little waste as possible. Now, even math experts have given up on finding a computer algorithm to answer this type of geometric problem. (2020-12-07)

One for all
AI-based evaluation of medical imaging data usually requires a specially developed algorithm for each task. Scientists from the German Cancer Research Center (DKFZ) have now presented a new method for configuring self-learning algorithms for a large number of different imaging datasets - without the need for specialist knowledge or very significant computing power. (2020-12-07)

New method uses artificial intelligence to study live cells
A new study combines label-free imaging with artificial intelligence to study unlabeled live cells. This method has promising applications for samples that need to be observed over long periods without the use of labels. (2020-12-07)

'Big data' enables first census of desert shrub
Researchers at The University of Texas at Austin leveraged computer algorithms and high-resolution survey data to conduct the first-ever creosote census - counting every creosote in a 135-square-mile conservation site in Nevada's Mojave Desert. The researchers discovered important new information about the plant species, but they also demonstrate how data techniques can improve on conventional methods for studying plant communities. (2020-12-07)

Study highlights strategies for boosting accuracy of personal genetic risk scores
As the consumer genetics industry rapidly expands, more and more people are turning to DNA-based services to learn their risk of developing a wide range of diseases. However, the risk scores from these genetic tests are not always as precise as they could be, according to a new study from Scripps Research. The scientists examine many approaches to calculating the scores and recommend that personal genomics organizations adopt standards that will raise the bar for accuracy. (2020-12-03)

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