Results 31 to 40 of about 1,734,839 (338)
Representation learning with reward prediction errors
Neurons, Behavior, Data analysis, and Theory, 2022 The Reward Prediction Error hypothesis proposes that phasic activity in the midbrain dopaminergic system reflects prediction errors needed for learning in reinforcement learning. Besides the well-documented association between dopamine and reward processing, dopamine is implicated in a variety of functions without a clear relationship to reward ...
Alexander, William H. +1 more
openaire +2 more sources
Leveled Certificateless Fully Homomorphic Encryption Schemes From Learning With Errors
IEEE Access, 2020 Fully homomorphic encryption (FHE) is a form of public-key encryption that allows the computation of arbitrary functions on encrypted data without decrypting the data. As a result, it is a useful tool with numerous applications.
Mingxiang Li
doaj +1 more source
Approximate Autonomous Quantum Error Correction with Reinforcement Learning
Physical Review Letters, 2023 Autonomous quantum error correction (AQEC) protects logical qubits by engineered dissipation and thus circumvents the necessity of frequent, error-prone measurement-feedback loops. Bosonic code spaces, where single-photon loss represents the dominant source of error, are promising candidates for AQEC due to their flexibility and controllability.
Yexiong Zeng +4 more
openaire +3 more sources
Predictive learning, prediction errors, and attention: evidence from event-related potentials and eye tracking [PDF]
, 2007 Prediction error (‘‘surprise’’) affects the rate of learning: We learn more rapidly about cues for which we initially make incorrect predictions than cues for which our initial predictions are correct.
A. J. Wills +4 more
core +1 more source
Alifmatika, 2023 Errors often occurred when students solve mathematical problems solving, exceedingly when students are faced with contextual story problems. Newman's procedural error analysis classified errors in solved story problems into five categories: reading ...
Anas Ma'ruf Annizar, Dewi Fatma Kumala
doaj +1 more source
Dynamical and Stationary Properties of On-line Learning from Finite Training Sets
, 2002 The dynamical and stationary properties of on-line learning from finite training sets are analysed using the cavity method. For large input dimensions, we derive equations for the macroscopic parameters, namely, the student-teacher correlation, the ...
A.C.C. Coolen +19 more
core +1 more source
On the concrete hardness of Learning with Errors
Journal of Mathematical Cryptology, 2015 The learning with errors (LWE) problem has become a central building block of modern cryptographic constructions. This work collects and presents hardness results for concrete instances of LWE.
Albrecht Martin R. +2 more
doaj +1 more source
STUDENTS’ ERROR ANALYSIS ON LINEAR PROGRAM BASED ON THE KIAT MODEL AND STUDENTS’ LEARNING INTEREST
Kalamatika, 2022 KIAT categorizes three types of mistakes: conceptual, procedural, and technical errors. This study analyzes student errors in solving mathematical problems on linear programming material based on student learning interests.
Jefrizal Hasyim +2 more
doaj +1 more source
Automatic error function learning with interpretable compositional networks
Annals of Mathematics and Artificial Intelligence, 2023 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Richoux, Florian +1 more
openaire +2 more sources
An MLWE-Based Cut-and-Choose Oblivious Transfer Protocol
EntropyThe existing lattice-based cut-and-choose oblivious transfer protocol is constructed based on the learning-with-errors (LWE) problem, which generally has the problem of inefficiency.
Yongli Tang +5 more
doaj +1 more source