Papers: SCOTUS – Trueskill Through Time

Martin-Quinn scores measure the the evolution of the ideal point of the justices of the U.S. supreme court.  The “ideal point” is a latent variable derived from voting records that intuitively resembles the concept of ideological bias.  The inference procedure is based on Markov Chain Monte Carlo.

Along these same lines there is the work of Lawrence Sirovich (who wrote the early papers applying PCA to human faces to construct “Eigenfaces”) in PNAS who computes a singular value decomposition of the voting matrix of the Rehnquist court, and finds a large latent factor that corresponds to liberal / conservative bias.

A pattern analysis of the second Rehnquist U.S. Supreme Court: Lawrence Sirovich PNAS 13 7432 (2003)

Another interesting work which appeared in NIPS a few years ago:

TrueSkill through time: Revisiting the History of Chess

by Pierre Dangautheir, Ralf Herbrich, Tom Minka, and Thore Graepel of Microsoft Research

How would Morphy or Capablanca fare against Kramnik, Kasparov, or the late Bobby Fischer? The authors developed a method for deducing the change in a player’s skill over time from their record of wins and losses.  It allows players who were never played each other (and who weren’t even alive at the same time) to be compared on the same scale.

I’m just surprised that they didn’t include Deep Thought / Blue

This paper is a great application of graphical models and belief propagation.