Browse Articles

Improving the classifier of the difficulty level of Sudoku.

The authors looked at different combinations of risk-adjusted return measures to determine which combination would provide an optimal return for investors. They found that different combinations performed better dependent on investment timeframe.

The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.

The authors looked at potential downstream effects of raising the minimum wage. Specifically they focused on taxable wages, employment, and firm counts.

The authors develop a method for detecting fake AI-generated images from real images.

The authors looked at variables associated with identity fraud in the US. They found that national unemployment rate and online banking usage are among significant variables that explain identity fraud.

The authors compare the predicted versus actual geyser eruption times for the Old Faithful and Beehive Geysers at Yellowstone National Park.

The authors explore how diversity in data sets contributes to bias in artificial intelligence.

Chess engines, or computer programs built to play chess, outperform even the best human players. Kaushikan and Park investigate the inner workings of these chess engines by studying popular chess engines' evaluations of which side of a chess match is most likely to win, and how this is affected by the number of pieces and controlled squares on each side.

The authors develop and test a machine learning algorithm for predicting diabetes diagnoses.