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Portfolio optimization is one of the essential fields of focus in finance. There has been an increasing demand for novel computational methods in this area to compute portfolios with better returns and lower risks in recent years. We present a novel computational method called Representation Portfolio Selection by redefining the distance matrix of financial assets using Representation Learning and Clustering algorithms for portfolio selection to increase diversification. RPS proposes a heuristic for getting closer to the optimal subset of assets. Using empirical results in this paper, we demonstrate that widely used portfolio optimization algorithms, such as Mean-Variance Optimization, Critical Line Algorithm, and Hierarchical Risk Parity can benefit from our asset subset selection.

As next-generation communication services and satellite systems expand across diverse frequency bands, there is a pressing need to use the spectrum as efficiently as possible. A possible strategy to achieve this is to facilitate the coexistence of different radio services, for example between telecommunication and microwave remote sensing systems. However, this approach could increase the risk of radio frequency interference (RFI) affecting passive microwave sensors, which are crucial for environmental and geoscience applications. Therefore, the availability of a testbed along with a dataset encompassing a diverse array of scenarios under a controlled environment is very important in order to study coexistence scenarios and reduce the risk of interference associated with them. This study presents a physical environmentally controlled testbed including a passive fully calibrated L-band radiometer with a digital back-end capable of collecting raw in-phase/quadrature (IQ) samples and an active fifth-generation (5G) wireless communication system with the capability of transmitting waveforms with advanced modulations. Various RFI situations such as in-band, transition band, and out-of-band transmission effects are quantified in terms of their effect on the measured brightness temperature. A detailed procedure and publicly accessible dataset are provided to help test the impact of wireless communication on passive sensing, enabling the scientific community to facilitate coexistence research and quantify interference effects on radiometers. This dataset includes publicly available raw radiometer and 5G communication samples along with preprocessed time-frequency representations and true brightness temperature data.