Results 111 to 120 of about 527,157 (233)
A Learning Model with Memory in the Financial Markets
International Journal of Finance &Economics, EarlyView.ABSTRACT Learning is central to a financial agent's aspiration to gain persistent strategic advantage in asset value maximisation. The implicit mechanism that transforms this aspiration into an observed value gain is the speed of error corrections (demonstrating, an agent's speed of learning) whilst facing increased uncertainty.
Shikta Singh +6 more
wiley +1 more source
Steiner Triple Systems With High Discrepancy
Journal of Combinatorial Designs, EarlyView.ABSTRACT In this paper, we initiate the study of discrepancy questions for combinatorial designs. Specifically, we show that, for every fixed r ≥ 3 $r\ge 3$ and n ≡ 1 , 3 ( mod 6 ) $n\equiv 1,3\,(\mathrm{mod}\,6)$, any r $r$‐colouring of the triples on [ n ] $[n]$ admits a Steiner triple system of order n $n$ with discrepancy Ω ( n 2 ) ${\rm{\Omega }}({
Lior Gishboliner +2 more
wiley +1 more source
Number Theory and Polynomials: The Mahler measure of algebraic numbers: a survey [PDF]
, 2008 Chris Smyth
openalex
New Difference Triangle Sets by a Field‐Programmable Gate Array‐Based Search Technique
Journal of Combinatorial Designs, EarlyView.ABSTRACT We provide some difference triangle sets with scopes that improve upon the best known values. These are found with purpose‐built digital circuits realized with field‐programmable gate arrays (FPGAs) rather than software algorithms running on general‐purpose processors.
Mohannad Shehadeh +2 more
wiley +1 more source
A General Approach to Dropout in Quantum Neural Networks
Advanced Quantum Technologies, EarlyView., 2023 Randomly dropping artificial neurons and all their connections in the training phase reduces overfitting issues in classical neural networks, thus improving performances on previously unseen data. The authors introduce different dropout strategies applied to quantum neural networks, learning models based on parametrized quantum circuits.
Francesco Scala +3 more
wiley +1 more source
On the Q $Q$‐Polynomial Property of Bipartite Graphs Admitting a Uniform Structure
Journal of Combinatorial Designs, EarlyView.ABSTRACT Let Γ ${\rm{\Gamma }}$ denote a finite, connected graph with vertex set X $X$. Fix x ∈ X $x\in X$ and let ε ≥ 3 $\varepsilon \ge 3$ denote the eccentricity of x $x$. For mutually distinct scalars { θ i * } i = 0 ε ${\{{\theta }_{i}^{* }\}}_{i=0}^{\varepsilon }$ define a diagonal matrix A * = A * ( θ 0 * , θ 1 * , … , θ ε * ) ∈ Mat X ( R ) ${A}^
Blas Fernández +3 more
wiley +1 more source
Benefits of Open Quantum Systems for Quantum Machine Learning
Advanced Quantum Technologies, EarlyView., 2023 Quantum machine learning (QML), poised to transform data processing, faces challenges from environmental noise and dissipation. While traditional efforts seek to combat these hindrances, this perspective proposes harnessing them for potential advantages. Surprisingly, under certain conditions, noise and dissipation can benefit QML.
María Laura Olivera‐Atencio +2 more
wiley +1 more source
Land Degradation &Development, EarlyView.ABSTRACT Soil disturbance resulting from forest harvesting activities can have significant and lasting environmental consequences, particularly in sensitive ecosystems such as Mediterranean forests. Skid trails, the routes used by machinery to extract timber, are among the most critical areas of impact, and their detection is critical for assessing ...
Francesco Latterini +9 more
wiley +1 more source
The commutative algebra of congruence ideals and applications to number theory [PDF]
Srikanth B. Iyengar +2 more
openalex +1 more source