Results 1 to 10 of about 3,377 (218)
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Oskar Ålund +2 more
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Differential Machine Learning [PDF]
Differential machine learning combines automatic adjoint differentiation (AAD) with modern machine learning (ML) in the context of risk management of financial Derivatives. We introduce novel algorithms for training fast, accurate pricing and risk approximations, online, in real-time, with convergence guarantees.
Brian Huge, Antoine Savine
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This research aims to explore the implementation of students' sensory learning styles in creating differentiated content and the factors that contribute to it. The research method used was a case study with a qualitative approach.
Erna Sulistianingrum +3 more
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Continual Learning with Differential Privacy [PDF]
The paper will appear at ...
Pradnya Desai +3 more
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Differential Temporal Difference Learning [PDF]
Value functions derived from Markov decision processes arise as a central component of algorithms as well as performance metrics in many statistics and engineering applications of machine learning techniques. Computation of the solution to the associated Bellman equations is challenging in most practical cases of interest.
Adithya M. Devraj +2 more
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Learning Differentially Private Mechanisms [PDF]
Differential privacy is a formal, mathematical definition of data privacy that has gained traction in academia, industry, and government. The task of correctly constructing differentially private algorithms is non-trivial, and mistakes have been made in foundational algorithms.
Subhajit Roy 0001 +2 more
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The article examines the issue of intra-school differentiation (Ukr. Transl. ‘внутрішньошкільна диференціація’) in primary education, actualized in the early 70s of the 20th century in Ukraine.
Tetiana Havrylenko
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This study aims to reveal the actualization of the principal's instructional leadership in carrying out differentiated learning that embodies students' well-being.
Nunuk Hariyati +4 more
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Learning With Differential Privacy [PDF]
The leakage of data might have an extreme effect on the personal level if it contains sensitive information. Common prevention methods like encryption-decryption, endpoint protection, intrusion detection systems are prone to leakage. Differential privacy comes to the rescue with a proper promise of protection against leakage, as it uses a randomized ...
Poushali Sengupta +2 more
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