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EFTA02702508Set 11

read on Sunday night. After the reading a few of the writers created through machine learning, the overall approach is came up to me and commented on my reading ... reading optimization, not machine-learned transformations. was short because the poems were short—and the attendees The primary research question is to try to isolate and codify knew i didn ... fear. To the objection that Godel took care of that for us. TUr- through machine learning—although a very simple type. ing points out that G0del took care of only

https://www.justice.gov/epstein/files/DataSet%2011/EFTA02702508.pdf

EFTA01783616Set 10

2016-08-235p2,080w

first Al assistant that helps you craft perfect emails. Boomerang Respondable uses machine learning algorithms trained on hundreds=of millions of messages to isolate what factors impact response rates ... your judgment says otherwise. Second, we're excited abo=t the prospect of using machine learning to provide actionable writing ad=ice based on data. Historically, authors of writing style ... transmit any message data anywhere, for any purpose. If yo= choose to enable advanced machine learning features, Boomerang transmi=s message data using enterprise-grade encryption, analyzes the message=data

https://www.justice.gov/epstein/files/DataSet%2010/EFTA01783616.pdf

EFTA01221384Set 9

undiscovered patterns and/or relationships in large databases. Data mining finds its roots in the Machine Learning community whereby academicians invented and developed artificial intelligence algorithms as a basis for machine ... there were many beneficial outcomes of those efforts. Among these were the advancements in machine learning technologies and algorithms. Through these efforts, along with advances in database technologies, data storage ... mined" to develop predictive models to guide future decision- making. • The field of machine learning has continued to evolve in the academic communities. New concepts, new algorithms and new computer

https://www.justice.gov/epstein/files/DataSet%209/EFTA01221384.pdf

EFTA00287327Set 9

years, we have seen the rise of the use of more powerful tools, including machine learning and inference aimed at algorithmic manipulation, with the target of influencing the thinking ... advanced tools to control, shape, forge and personalize information, from ads to news reports. Machine learning, in conjunction with active learning, expected value decision making, and optimization of allocations ... written by your close friend. • Adaptive botnets, worms, or viruses that use modern machine learning techniques to learn and adapt. Viruses and botnets already cause a huge amount of damage

https://www.justice.gov/epstein/files/DataSet%209/EFTA00287327.pdf

EFTA01612888Set 10

extending the reach of collaborations and sharing beyond local networks. 8 EFTA01612895 6.2 Machine Learning With the rapid improvement in computational power and machine learning algorithms, blockchain technol ... compensate an Artificial Intelligence (AI) service provider for the development and execution of novel machine learning algorithms. For example, developing machine learning algorithms that can look at a radiology image ... radiology images to the blockchain. An AI service provider that specializes in developing novel machine learning algorithms with which the hospital has partnerships would be allowed to rim their algorithm

https://www.justice.gov/epstein/files/DataSet%2010/EFTA01612888.pdf

EFTA01023686Set 9

2018-09-096p3,048w

machine that controls them instead. We are stuck in this digital mindset—believing that machine learning, deep learning, etc. is just a way to cultivate better algorithms that the usual ... Quantum Computer Scientist Takes on the Cosmos. I am working on problems of quantum machine learning, developing novel protocols that allow quantum systems to find patterns in nature that ... revealed by classical machine learning algorithms. I am also working with experimentalists to implement these quantum machine learning protocols on photonic and superconducting quantum computers. As part of this research

https://www.justice.gov/epstein/files/DataSet%209/EFTA01023686.pdf

EFTA01189563Set 9

2013-10-105p1,028w

part of the coursework. This course will run for eight weeks. Find out more Machine Learning Andrew Ng Starting October 14th This course provides a broad introduction to machine learning ... data mining, and statistical pattern recognition. Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has enabled the development

https://www.justice.gov/epstein/files/DataSet%209/EFTA01189563.pdf

EFTA01813414Set 10

2010-06-222p622w

presented: "Open Problems in Reproducibility for Massive Datasets" June 25: International Conference on Machine Learning (top machine learning conference). Giving Workshop Keynote. Title: "Reproducible Research in Machine Learning" (Haifa, Israel

https://www.justice.gov/epstein/files/DataSet%2010/EFTA01813414.pdf

EFTA01813452Set 10

2010-06-222p605w

presented: "Open Problems in Reproducibility for Massive Datasets" June 25: International Conference on Machine Learning (top machine learning conference). Giving Workshop Keynote. Title: "Reproducible Research in Machine Learning" (Haifa, Israel

https://www.justice.gov/epstein/files/DataSet%2010/EFTA01813452.pdf

EFTA01103465Set 9

2013-12-0230p11,241w

connection to the Nao robot • coauthor of Engineering General Intelligence Dr. Eddie Monroe OpenCog machine learning engineer at Novamente LLC Dr. Matthew We' co-developer of the mathematics underlying OpenCog ... take the next step, and push from the narrow AI style use of machine learning tools to analyze individual genomic datasets or small collections of genomic dataset, to the more ... Learning). These systems conduct information extraction from texts and images via a combination of machine learning algorithms. A very promising approach would be to integrate standard machine learning algorithms with

https://www.justice.gov/epstein/files/DataSet%209/EFTA01103465.pdf

EFTA01125174Set 9

phenotype classification of whole- genome sequenced samples with boolean models derived via MOSES supervised machine learning (Mike Duncan & Ben Goertzel) EFTA01125181 abstract • A boolean classification function was constructed using ... novel supervised machine learning algorithm to categorize healthy from chronically ill geriatric subjects. From an evenly divided sample set of 783 subjects, a population of boolean functions consisting on average ... rs7531 ref (0) It (1) program control case (true) value (false) EFTA01125184 supervised machine learning strategy • A cross validation strategy is used where the data set is randomly partitioned into

https://www.justice.gov/epstein/files/DataSet%209/EFTA01125174.pdf

EFTA00704552Set 9

2017-08-039p3,304w

health and disease. EFTA00704552 They aim to develop personalized nutrition and personalized medicine using machine learning, computational biology, probabilistic modeling, and analysis of heterogeneous genomic and clinical data. Eran Segal ... middle class, demand for medical imaging diagnosis will outstrip the supply of radiologists. Using machine learning, Zebra has created an algorithm that it says can help meet the excess demand ... Massachusetts Institute of Technology. (immune drug discovery w AI) CytoReason is using its machine-learning model of the immune-system to discover complex patterns in biological data. Founded

https://www.justice.gov/epstein/files/DataSet%209/EFTA00704552.pdf

EFTA01039044Set 9

2017-08-029p3,281w

health and disease. They aim to develop personalized nutrition and personalized medicine using machine learning, computational biology, probabilistic modeling, and analysis of heterogeneous genomic and clinical data. Eran Segal ... middle class, demand for medical imaging diagnosis will outstrip the supply of radiologists. Using machine learning, Zebra has created an algorithm that it says can help meet the excess demand ... Massachusetts Institute of Technology. EFTA01039045 (immune drug discovery w AI) CytoReason is using its machine-learning model of the immune-system to discover complex patterns in biological data. Founded

https://www.justice.gov/epstein/files/DataSet%209/EFTA01039044.pdf

EFTA00804028Set 9

health and disease. They aim to develop personalized nutrition and personalized medicine using machine learning, computational biology, probabilistic modeling, and analysis of heterogeneous genomic and clinical data. Eran Segal ... middle class, demand for medical imaging diagnosis will outstrip the supply of radiologists. Using machine learning, Zebra has created an algorithm that it says can help meet the excess demand ... Massachusetts Institute of Technology. (immune drug discovery w Al) CytoReason is using its machine-learning model of the immune-system to discover complex patterns in biological data. Founded

https://www.justice.gov/epstein/files/DataSet%209/EFTA00804028.pdf

EFTA00646236Set 9

2017-08-0210p3,432w

health and disease. They aim to develop personalized nutrition and personalized medicine using machine learning, computational biology, probabilistic modeling, and analysis of heterogeneous genomic and clinical data. EFTA00646237 Eran Segal ... middle class, demand for medical imaging diagnosis will outstrip the supply of radiologists. Using machine learning, Zebra has created an algorithm that it says can help meet the excess demand ... Massachusetts Institute of Technology. (immune drug discovery w AI) CytoReason is using its machine-learning model of the immune-system to discover complex patterns in biological data. Founded

https://www.justice.gov/epstein/files/DataSet%209/EFTA00646236.pdf

EFTA00285853Set 9

2019-04-1011p7,239w

ALERT Petviashvili founded a firm called NewsAlpha that uses Capital Flowing to Al Startup machine-learning techniques to perform risk-factor and news- A startup equity manager that employs artificial ... looked so appealing. A spokesman for Tiger Manage- of an "Al fund that uses machine learning and mathematics" ment declined to comment. While artificial intelligence and machine learning often ... years. While many of those firms subse- ing broad decision-making processes and machine learning as quently bought out Tiger's interest or shut down, the 20 or so suitable

https://www.justice.gov/epstein/files/DataSet%209/EFTA00285853.pdf

EFTA01087827Set 9

algebra for applications in signal and image processing, computer vision, graphics engineering, robotics and machine learning. Prof. Eduardo Bayro-Corrochano Camera Culture Group, Media Lab. MIT Course ... algebra for applications in signal and image processing, computer vision, graphics engineering, robotics and machine learning. We will show that this mathematical system keeps our intuitions and insight ... applications in signal and image processing, filtering, estimation and interpolation, neural networks and machine learning, PCA and big data, graphics engineering, stereo vision, range data, laser, stereo-omnidirectional and odometry

https://www.justice.gov/epstein/files/DataSet%209/EFTA01087827.pdf

EFTA01008124Set 9

2017-09-258p3,646w

What he was doing inadvertently in his talk was backing into a very interesting machine learning problem as noted by one of the more mathematically inclined investors that happened ... science, serendipity is pretty important. Right now in life science, the roles of both machine learning and semiconductors/mobile are so far afield from life sciences and so immature as tooling ... mutations is pretty intense. The role of computer modeling is to develop tools through machine learning that could help to combine DNA and bioelectrics to create specific cells "on demand

https://www.justice.gov/epstein/files/DataSet%209/EFTA01008124.pdf

EFTA00824156Set 9

2016-07-103p1,548w

same group, slower development often indicates defects, of course.) Another support comes from machine learning: we find that the same learning functions can learn visual and auditory pattern recognition ... stuff is something nobody could do a few months ago: http:/hvww.creativeai.net/pests/Mv4WG6rdzAerZF7ch/synthesizing-preferred-inputs-via-deep-generator- networks A machine learning program that can learn how to play an Atari game without any human supervision

https://www.justice.gov/epstein/files/DataSet%209/EFTA00824156.pdf

EFTA00824159Set 9

2016-07-103p1,498w

same group, slower development often indicates defects, of course.) Another support comes from machine learning: we find that the same learning functions can learn visual and auditory pattern recognition ... stuff is something nobody could do a few months ago: http:/Avww.creativeai.net/posts/Mv4WG6rdzAerZF7ch/synthesizing-preferred-inputs-via-deep-generator- networks A machine learning program that can learn how to play an Atari game without any human supervision

https://www.justice.gov/epstein/files/DataSet%209/EFTA00824159.pdf

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Corpus: 1990-03-17 – 2025-12-01

December 2025

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Results by Dataset318 total

Set 8

2

Set 9

213

Set 10

50

Set 11

53