6 papers
Financially Guided Deep Portfolio Optimization
Rahul Fernandes, Travis Desell
Portfolio optimization in real-world financial markets is notoriously difficult due to non-stationarity, noisy data, and high transaction costs. Standard predict-then-optimize meth…
Domain Feature Collapse: Implications for Out-of-Distribution Detection and Solutions
Hong Yang, Devroop Kar, Qi Yu +2
Why do state-of-the-art OOD detection methods exhibit catastrophic failure when models are trained on single-domain datasets? We provide the first theoretical explanation for this…
Investigating Quantum Circuit Designs Using Neuro-Evolution
Devroop Kar, Daniel Krutz, Travis Desell
Designing effective quantum circuits remains a central challenge in quantum computing, as circuit structure strongly influences expressivity, trainability, and hardware feasibility…
Can We Ignore Labels In Out of Distribution Detection?
Hong Yang, Qi Yu, Travis Desell
Out-of-distribution (OOD) detection methods have recently become more prominent, serving as a core element in safety-critical autonomous systems. One major purpose of OOD detection…
Class Incremental Continual Learning with Self-Organizing Maps and Variational Autoencoders Using Synthetic Replay
Pujan Thapa, Alexander Ororbia, Travis Desell
This work introduces a novel generative continual learning framework based on self-organizing maps (SOMs) and variational autoencoders (VAEs) to enable memory-efficient replay, eli…
Directly Learning Stock Trading Strategies Through Profit Guided Loss Functions
Devroop Kar, Zimeng Lyu, Sheeraja Rajakrishnan +4
Stock trading has always been a challenging task due to the highly volatile nature of the stock market. Making sound trading decisions to generate profit is particularly difficult…