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Found 8 papers, 0 papers with code
Behavioral Sequence Modeling with Ensemble Learning
We investigate the use of sequence analysis for behavior modeling, emphasizing that sequential context often outweighs the value of aggregate features in understanding human behavior.
AI in Investment Analysis: LLMs for Equity Stock Ratings
Investment Analysis is a cornerstone of the Financial Services industry.
Ensemble Methods for Sequence Classification with Hidden Markov Models
We present a lightweight approach to sequence classification using Ensemble Methods for Hidden Markov Models (HMMs).
Synthetic Data Applications in Finance
Synthetic data has made tremendous strides in various commercial settings including finance, healthcare, and virtual reality.
Visual Time Series Forecasting: An Image-driven Approach
In this work, we address time-series forecasting as a computer vision task.
Visual Time Series Forecasting: An Image-driven Approach
In this work, we leverage advances in deep learning to extend the field of time series forecasting to a visual setting.
Debiasing classifiers: is reality at variance with expectation?
We present an empirical study of debiasing methods for classifiers, showing that debiasers often fail in practice to generalize out-of-sample, and can in fact make fairness worse rather than better.
Cross-Domain Perceptual Reward Functions
One problem with this approach is that we typically need to redefine the rewards each time the goal changes, which often requires some understanding of the solution in the agents environment.
