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Found 7 papers, 0 papers with code
Neural Network Approach to Portfolio Optimization with Leverage Constraints:a Case Study on High Inflation Investment
We establish mathematically that the LFNN approximation can yield a solution that is arbitrarily close to the solution of the original optimal control problem with bounded leverage.
A parsimonious neural network approach to solve portfolio optimization problems without using dynamic programming
We present a parsimonious neural network approach, which does not rely on dynamic programming techniques, to solve dynamic portfolio optimization problems subject to multiple investment constraints.
A Composite T60 Regression and Classification Approach for Speech Dereverberation
More specifically, we develop a joint learning approach that uses a composite T60 module and a separate dereverberation module to simultaneously perform reverberation time estimation and dereverberation.
Optimal Asset Allocation For Outperforming A Stochastic Benchmark Target
The proposed framework is illustrated with the asset allocation problem in the accumulation phase of a defined contribution pension plan, with the goal of achieving a higher terminal wealth than a stochastic benchmark.
EREL Selection using Morphological Relation
In the first round, the pattern in a set of EREL regions is analyzed and used to generate an approximate luminal region.
Nonsmooth Frank-Wolfe using Uniform Affine Approximations
Frank-Wolfe methods (FW) have gained significant interest in the machine learning community due to its ability to efficiently solve large problems that admit a sparse structure (e. g. sparse vectors and low-rank matrices).
Projection Free Rank-Drop Steps
To address this issue, we propose a rank-drop method for nuclear norm constrained problems.
