Results 31 to 40 of about 1,068,320 (275)

Technology assessment of advanced automation for space missions [PDF]

, 1982
Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis ...

core   +1 more source

Exploiting the structure effectively and efficiently in low rank matrix recovery

, 2018
Low rank model arises from a wide range of applications, including machine learning, signal processing, computer algebra, computer vision, and imaging science.
Absil, Agarwal, Ahmed, Alter, Amelunxen, Beck, Blanchard, Blumensath, Boumal, Boyd, Bunk, Cai, Cai, Cai, Cai, Cai, Cai, Candes, Candes, Candes, Candes, Candes, Candès, Candès, Candès, Candès, Carmon, Chandrasekaran, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Combettes, Davenport, Davenport, Ding, Donoho, Fazel, Ge, Ge, Ge, Goldberg, Gross, Hardt, Harrison, Huang, Jaggi, Jain, Jain, Ji, Jin, Keshavan, Kim, Kliesch, Koltchinskii, Krim, Kueng, Lanman, Li, Li, Lin, Ling, Ling, Liu, Liu, Lustig, Ma, Miao, Mishra, Mishra, Mishra, Mobahi, Mu, Negahban, Netrapalli, Ngo, Potter, Qu, Recht, Recht, Schermelleh, Srebro, Strohmer, Sun, Sun, Tanner, Tanner, Tao, Tharrault, Toh, Toh, Tomasi, Tu, Vandereycken, Wang, Wei, Wei, Wei, Wen, WenHuang, Xu, Yi, Zhang, Zhang, Zheng   +109 more
core   +2 more sources

Next‐generation proteomics improves lung cancer risk prediction

Molecular Oncology, EarlyView.
This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj, Clara Frick, Ben Schöttker, Bernd Holleczek, Hermann Brenner   +4 more
wiley   +1 more source

Developing evidence‐based, cost‐effective P4 cancer medicine for driving innovation in prevention, therapeutics, patient care and reducing healthcare inequalities

Molecular Oncology, EarlyView.
The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg, Joachim von Braun, Julio Celis, Anton Berns, Michael Baumann, Tit Albreht, Nancy Abou‐Zeid, Vanderlei Bagnato, Christian Brandts, Chien‐Jen Chen, Massimiliano di Pietro, Manjit Dosanjh, Thomas Dubois, Alexander Eggermont, Angelika Eggert, Ingemar Ernberg, Sara Faithfull, Johannes Förner, Stefan Fröhling, Manuel Heitor, Leroy Hood, Wei Jiang, Bengt Jönsson, Ravi Kannan, Maria Leptin, Su Li, Peter Lindgren, Douglas Lowy, Jun Ma, Alex Markham, Péter Nagy, Simon Oberst, M. Iqbal Parker, Danielle Rodin, Kevin Ryan, Joachim Schüz, Richard Sullivan, Josep Tabernero, Peter Turkson, Oliver Várhelyi, Harold Varmus, Chijie Wang, Elisabete Weiderpass, Nils Wilking   +43 more
wiley   +1 more source

How Much Information is in a Jet?

, 2017
Machine learning techniques are increasingly being applied toward data analyses at the Large Hadron Collider, especially with applications for discrimination of jets with different originating particles.
Datta, Kaustuv, Larkoski, Andrew
core   +1 more source

Integrating games and machine learning in the undergraduate computer science classroom [PDF]

Proceedings of the 3rd international conference on Game development in computer science education, 2008
A student will be more likely motivated to pursue a field of study if they encounter relevant and interesting challenges early in their studies. The authors are PIs on two NSF funded course curriculum development projects (CCLI). Each project seeks to provide compelling curricular modules for use in the Computer Science classroom starting as soon as CS
Scott A. Wallace, Ingrid Russell, Zdravko Markov   +2 more
openaire   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Improving prediction of hepatocellular carcinoma in chronic hepatitis B by machine learning: Productive relationship of medicine with computer science [PDF]

, 2023
Terry Cheuk‐Fung Yip, Cihan Yurdaydın
openalex   +1 more source

By-passing the Kohn-Sham equations with machine learning

, 2017
Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields, ranging from materials science to biochemistry to astrophysics.
Brockherde, Felix, Burke, Kieron, Li, Li, Müller, Klaus-Robert, Tuckerman, Mark E., Vogt, Leslie   +5 more
core   +3 more sources

Rethinking plastic waste: innovations in enzymatic breakdown of oil‐based polyesters and bioplastics

FEBS Open Bio, EarlyView.
Plastic pollution remains a critical environmental challenge, and current mechanical and chemical recycling methods are insufficient to achieve a fully circular economy. This review highlights recent breakthroughs in the enzymatic depolymerization of both oil‐derived polyesters and bioplastics, including high‐throughput protein engineering, de novo ...
Elena Rosini, Nicolò Antonelli, Gianluca Molla   +2 more
wiley   +1 more source