IBM Proposes Effective ML Drift Detection Via Weak Data Slices (FAKE BLOG)
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Generated: 9/6/2021
IBM Proposes Effective ML Drift Detection Via Weak Data Slices Based on the PDS Model
SAN FRANCISCO—The IBM Research (IBM) team has developed a machine learning (ML) framework for accurate drift detection in Massive MIMO systems. The framework leverages deep neural networks as well as random projection and weak data slices to detect accurate state-of-the-art ML drift, which increases system capacity and reduces computational complexity by 15X compared to the conventional algorithms. The research was presented in a paper entitled “Deep Drift Detection with Weighted Sum-Product Nets: A Deep Machine Learning Approach for Linear Drift Detection,” by Guoping Tang and Yan Wang, as well as in the IBM Machine Learning Blog.
Drift detection is the process of identifying and removing unknown changes in a system that may cause data errors in the system. This process may involve detecting abrupt changes in the system and then understanding, removing, and replacing it; or it may involve detecting the unknown change and eliminating or replacing it while maintaining overall system performance. Drift detection is an important process that plays a significant role in ensuring that systems maintain high-quality performance. Accurate data management and robust, efficient system operation are critical for a successful, high-quality system.
Drift detection is a fundamental ML task that has been widely studied in the past few decades. However, most previous methods cannot effectively identify and eliminate abrupt changes in the system with good accuracy. They are very sensitive to data outliers and data noise. As a result, they are usually time-consuming to implement.
Drift detection is a fundamental ML task that has been widely studied in the past few decades. However, most previous methods cannot effectively identify and eliminate abrupt changes in the system with good accuracy. They are very sensitive to data outliers and data noise. As a result, they are usually time-consuming to implement.
The method proposed in the paper combines an innovative ML architecture with powerful outlier detection and drift detection algorithms to accurately identify and eliminate abrupt changes in the system. The method has a learning rate of 0.001. The algorithm has been evaluated against a set of well-established drift detection algorithms. It has a detection rate of 99.9%, while those algorithms have detection rates of 92.2%–99.90%. Moreover, the method is extremely effective in the presence of data outliers. The method is able to identify the abrupt changes and remove them, while maintaining the overall system performance.
The paper “Deep Drift Detection with Weighted Sum-Product Nets: A Deep Machine Learning Approach for Linear Drift Detection,” was published in an early online version of the Journal of Machine Learning Research (JMLR). The abstract and full paper describing the research can be found here.
About IBM Research
IBM Research is a global not-for-profit organization dedicated to helping humanity address some of its most intractable challenges, including finding new ways to harness the power of data in order to advance understanding, solve global problems, and build a more sustainable future. With a multidisciplinary approach to innovation, IBM Research leads the world in some of the world’s most important and exciting research, including creating data-driven solutions for a broad spectrum of business challenges, solving complex scientific and medical problems, developing innovative technologies to help solve the world’s energy and climate challenges, developing new healthcare solutions, and developing new, more secure infrastructure for the Internet, Cloud, and mobile computing.
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(Date:12/8/2016)... 8, 2016 Biocon ... today that it has been recognized by the American College of ... Blood and Blood Products (ABC/LifeNet) have been awarded the ... to lead the development of new approaches to treatment and . ... The honor comes on the heels of several highly ...
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SAN FRANCISCO—The IBM Research (IBM) team has developed a machine learning (ML) framework for accurate drift detection in Massive MIMO systems. The framework leverages deep neural networks as well as random projection and weak data slices to detect accurate state-of-the-art ML drift, which increases system capacity and reduces computational complexity by 15X compared to the conventional algorithms. The research was presented in a paper entitled “Deep Drift Detection with Weighted Sum-Product Nets: A Deep Machine Learning Approach for Linear Drift Detection,” by Guoping Tang and Yan Wang, as well as in the IBM Machine Learning Blog.
Drift detection is the process of identifying and removing unknown changes in a system that may cause data errors in the system. This process may involve detecting abrupt changes in the system and then understanding, removing, and replacing it; or it may involve detecting the unknown change and eliminating or replacing it while maintaining overall system performance. Drift detection is an important process that plays a significant role in ensuring that systems maintain high-quality performance. Accurate data management and robust, efficient system operation are critical for a successful, high-quality system.
Drift detection is a fundamental ML task that has been widely studied in the past few decades. However, most previous methods cannot effectively identify and eliminate abrupt changes in the system with good accuracy. They are very sensitive to data outliers and data noise. As a result, they are usually time-consuming to implement.
Drift detection is a fundamental ML task that has been widely studied in the past few decades. However, most previous methods cannot effectively identify and eliminate abrupt changes in the system with good accuracy. They are very sensitive to data outliers and data noise. As a result, they are usually time-consuming to implement.
The method proposed in the paper combines an innovative ML architecture with powerful outlier detection and drift detection algorithms to accurately identify and eliminate abrupt changes in the system. The method has a learning rate of 0.001. The algorithm has been evaluated against a set of well-established drift detection algorithms. It has a detection rate of 99.9%, while those algorithms have detection rates of 92.2%–99.90%. Moreover, the method is extremely effective in the presence of data outliers. The method is able to identify the abrupt changes and remove them, while maintaining the overall system performance.
The paper “Deep Drift Detection with Weighted Sum-Product Nets: A Deep Machine Learning Approach for Linear Drift Detection,” was published in an early online version of the Journal of Machine Learning Research (JMLR). The abstract and full paper describing the research can be found here.
About IBM Research
IBM Research is a global not-for-profit organization dedicated to helping humanity address some of its most intractable challenges, including finding new ways to harness the power of data in order to advance understanding, solve global problems, and build a more sustainable future. With a multidisciplinary approach to innovation, IBM Research leads the world in some of the world’s most important and exciting research, including creating data-driven solutions for a broad spectrum of business challenges, solving complex scientific and medical problems, developing innovative technologies to help solve the world’s energy and climate challenges, developing new healthcare solutions, and developing new, more secure infrastructure for the Internet, Cloud, and mobile computing.
(Date:12/9/2016)... , Dec. 9, 2016 ... ... ... for the next generation of Xbird®, an innovative technology used by ... will be available this quarter in store and online at ... a limited time. The Inventors will also demonstrate the product for the ...
(Date:12/8/2016)... ... 08, 2016 , ... Today’s patients are being served at a ... that best possible decision and care while being a strategic part of the ... , It was that time of year again ...
(Date:12/8/2016)... ... December 08, 2016 , ... The Pennsylvania ... with the Pennsylvania Chapter of the American Academy of Family Physicians. This is ... memberships provide unlimited access to exclusive health information, this includes ...
(Date:12/8/2016)... 8, 2016 KEY FINDINGS The global ... 2030" report revealed that over 70 million metric tons of avoidable Achieve ... emissions in 2015. This represents ... are due to the growing awareness for the critical importance of adopting and ...
(Date:12/8/2016)... , ... December 08, 2015 , ... ... serve up to 4,000 attendees at its annual Meeting and User Conference (UMS). This ... their learning within the exhibit hall. The San Diego-based company is experiencing a ...
(Date:12/8/2016)... 8, 2016 Necma Vocal Health has been recognized by ... Ministry for innovation and entrepreneurship, to celebrate achievements ... of more than $1 billion in annual sales. This recognition highlights the ... was received from the South Korean Ministry of Science and I...
(Date:12/8/2016)... 8, 2016 Biocon ... today that it has been recognized by the American College of ... Blood and Blood Products (ABC/LifeNet) have been awarded the ... to lead the development of new approaches to treatment and . ... The honor comes on the heels of several highly ...
(Date:12/8/2016)... Dec. 8, 2016 Pennsylvania ... Secretary of Drug and Alcohol Programs, ... at its upcoming annual meeting in San Antonio,s ... with a dual diagnosis of drug abuse and mental health, as defined ... management for treatment and management of the dual diagnosis, and ...on metric tons of avoidable Achieve ... emissions in 2015. This represents ... are due to the growing awareness for the critical importance of adopting and ...
(Date:12/8/2016)... , ... December 08, 2015 , ... ... serve up to 4,000 attendees at its annual Meeting and User Conference (UMS). This ... their learning within the exhibit hall. The San Diego-based company is experiencing a ...
(Date:12/8/2016)... 8, 2016 Necma Vocal Health has been recognized by ... Ministry for innovation and entrepreneurship, to celebrate achievements ... of more than $1 billion in annual sales. This recognition highlights the ... was received from the South Korean Ministry of Science and I...
(Date:12/8/2016)... 8, 2016 Biocon ... today that it has been recognized by the American College of ... Blood and Blood Products (ABC/LifeNet) have been awarded the ... to lead the development of new approaches to treatment and . ... The honor comes on the heels of several highly ...
(Date:12/8/2016)... Dec. 8, 2016 Pennsylvania ... Secretary of Drug and Alcohol Programs, ... at its upcoming annual meeting in San Antonio,s ... with a dual diagnosis of drug abuse and mental health, as defined ... management for treatment and management of the dual diagnosis, and ...
(Date:12/8/2016)... -- Eli Lilly and Company (NYSE: ... markets, today announced the appointment of David D. ... to the company 's Pharmaceutical and Medical Devices group ... and previously as president and CEO of Janssen Scientific ... Mr. Kravis brings a vast, global ...
(Date:12/8/2016)... 8, 2016 Eli Lilly and Company (NYSE: ... business - Biomedical Materials - ... biopharmaceutical company. , Lilly ... a drug known as Ocrevus to treat multiple ... types of cancers. The U.S. Food ... is available to patients who have not benefited from ...
(Date:12/8/2016)... 2016 According to the American ... community, a new study supports the notion that ... and healthy behavior patterns in children. The study was ... Play an important role in childhood development. "Our children's ...