no code implementations • 6 Apr 2024 • Kevin Du, Vésteinn Snæbjarnarson, Niklas Stoehr, Jennifer C. White, Aaron Schein, Ryan Cotterell
To answer a question, language models often need to integrate prior knowledge learned during pretraining and new information presented in context.
1 code implementation • 10 Mar 2024 • John Hood, Aaron Schein
This paper introduces AL$\ell_0$CORE, a new form of probabilistic non-negative tensor decomposition.
no code implementations • 14 Dec 2023 • Sean O'Hagan, Aaron Schein
Much of social science is centered around terms like ``ideology'' or ``power'', which generally elude precise definition, and whose contextual meanings are trapped in surrounding language.
1 code implementation • 8 Dec 2022 • Niklas Stoehr, Benjamin J. Radford, Ryan Cotterell, Aaron Schein
For discrete data, SSMs commonly do so through a state-to-action emission matrix and a state-to-state transition matrix.
1 code implementation • 8 Oct 2022 • Niklas Stoehr, Lucas Torroba Hennigen, Josef Valvoda, Robert West, Ryan Cotterell, Aaron Schein
It is based only on the action category ("what") and disregards the subject ("who") and object ("to whom") of an event, as well as contextual information, like associated casualty count, that should contribute to the perception of an event's "intensity".
no code implementations • 12 Jun 2021 • Aaron Schein, Anjali Nagulpally, Hanna Wallach, Patrick Flaherty
We present a new non-negative matrix factorization model for $(0, 1)$ bounded-support data based on the doubly non-central beta (DNCB) distribution, a generalization of the beta distribution.
1 code implementation • NeurIPS 2019 • Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna Wallach
This paper presents the Poisson-randomized gamma dynamical system (PRGDS), a model for sequentially observed count tensors that encodes a strong inductive bias toward sparsity and burstiness.
1 code implementation • 22 Mar 2018 • Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna Wallach
We present a general method for privacy-preserving Bayesian inference in Poisson factorization, a broad class of models that includes some of the most widely used models in the social sciences.
1 code implementation • 19 Jan 2017 • Aaron Schein, Mingyuan Zhou, Hanna Wallach
We introduce a new dynamical system for sequentially observed multivariate count data.
1 code implementation • NeurIPS 2016 • Aaron Schein, Hanna Wallach, Mingyuan Zhou
This paper presents a dynamical system based on the Poisson-Gamma construction for sequentially observed multivariate count data.
1 code implementation • 6 Jun 2016 • Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna Wallach
We introduce Bayesian Poisson Tucker decomposition (BPTD) for modeling country--country interaction event data.
1 code implementation • 10 Jun 2015 • Aaron Schein, John Paisley, David M. Blei, Hanna Wallach
We demonstrate that our model's predictive performance is better than that of standard non-negative tensor factorization methods.
no code implementations • 15 Nov 2013 • Aaron Schein, Juston Moore, Hanna Wallach
Correlations between anomalous activity patterns can yield pertinent information about complex social processes: a significant deviation from normal behavior, exhibited simultaneously by multiple pairs of actors, provides evidence for some underlying relationship involving those pairs---i. e., a multilateral relation.
no code implementations • LREC 2012 • Keith J. Miller, Elizabeth Schroeder Richerson, Sarah McLeod, James Finley, Aaron Schein
This paper describes different aspects of an open competition to evaluate multicultural name matching software, including the contest design, development of the test data, different phases of the competition, behavior of the participating teams, results of the competition, and lessons learned throughout.