33 citations · 54 across the 5 of their papers we have counts for
5 papers
TopEx: Topic-based Explanations for Model Comparison
Shreya Havaldar, Adam Stein, Eric Wong +1
Meaningfully comparing language models is challenging with current explanation methods. Current explanations are overwhelming for humans due to large vocabularies or incomparable a…
Bayesian aggregation of two forecasts in the partial information framework
Philip Ernst, Robin Pemantle, Ville Satopaa +1
We generalize the results of \cite{SPU, SJPU} by showing how the Gaussian aggregator may be computed in a setting where parameter estimation is not required. We proceed to provide…
Combining Probability Forecasts and Understanding Probability Extremizing through Information Diversity
Ville Satopää, Robin Pemantle, Lyle Ungar
Randomness in scientific estimation is generally assumed to arise from unmeasured or uncontrolled factors. However, when combining subjective probability estimates, heterogeneity s…
Probability aggregation in time-series: Dynamic hierarchical modeling of sparse expert beliefs
Ville A. Satopää, Shane T. Jensen, Barbara A. Mellers +2
Most subjective probability aggregation procedures use a single probability judgment from each expert, even though it is common for experts studying real problems to update their p…
Spectral dimensionality reduction for HMMs
Dean P. Foster, Jordan Rodu, Lyle H. Ungar
Hidden Markov Models (HMMs) can be accurately approximated using co-occurrence frequencies of pairs and triples of observations by using a fast spectral method in contrast to the u…