4 citations · 8 across the 9 of their papers we have counts for
9 papers
Machine Learning and Hamilton-Jacobi-Bellman Equation for Optimal Decumulation: a Comparison Study
Marc Chen, Mohammad Shirazi, Peter A. Forsyth +1
We propose a novel data-driven neural network (NN) optimization framework for solving an optimal stochastic control problem under stochastic constraints. Customized activation func…
Neural Network Approach to Portfolio Optimization with Leverage Constraints:a Case Study on High Inflation Investment
Chendi Ni, Yuying Li, Peter A. Forsyth
Motivated by the current global high inflation scenario, we aim to discover a dynamic multi-period allocation strategy to optimally outperform a passive benchmark while adhering to…
A parsimonious neural network approach to solve portfolio optimization problems without using dynamic programming
Pieter M. van Staden, Peter A. Forsyth, Yuying Li
We present a parsimonious neural network approach, which does not rely on dynamic programming techniques, to solve dynamic portfolio optimization problems subject to multiple inves…
Optimal Asset Allocation For Outperforming A Stochastic Benchmark Target
Chendi Ni, Yuying Li, Peter Forsyth +1
We propose a data-driven Neural Network (NN) optimization framework to determine the optimal multi-period dynamic asset allocation strategy for outperforming a general stochastic t…
Quantum walk inspired algorithm for graph similarity and isomorphism
Callum Schofield, Jingbo B. Wang, Yuying Li
Large scale complex systems, such as social networks, electrical power grid, database structure, consumption pattern or brain connectivity, are often modeled using network graphs.…
EREL Selection using Morphological Relation
Yuying Li, Mehdi Faraji
This work concentrates on Extremal Regions of Extremum Level (EREL) selection. EREL is a recently proposed feature detector aiming at detecting regions from a set of extremal regio…
Nonsmooth Frank-Wolfe using Uniform Affine Approximations
Edward Cheung, Yuying Li
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.…
Are target date funds dinosaurs? Failure to adapt can lead to extinction
Peter A. Forsyth, Yuying Li, Kenneth R. Vetzal
Investors in Target Date Funds are automatically switched from high risk to low risk assets as their retirements approach. Such funds have become very popular, but our analysis bri…
Projection Free Rank-Drop Steps
Edward Cheung, Yuying Li
The Frank-Wolfe (FW) algorithm has been widely used in solving nuclear norm constrained problems, since it does not require projections. However, FW often yields high rank intermed…