9 citations · 11 across the 3 of their papers we have counts for
3 papers
cs.LG2010
A Geometric View of Conjugate Priors
Arvind Agarwal, Hal Daume
In Bayesian machine learning, conjugate priors are popular, mostly due to mathematical convenience. In this paper, we show that there are deeper reasons for choosing a conjugate pr…
cs.LG2010★ 2 cited
A Unified Algorithmic Framework for Multi-Dimensional Scaling
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasubramanian
In this paper, we propose a unified algorithmic framework for solving many known variants of \mds. Our algorithm is a simple iterative scheme with guaranteed convergence, and is \e…
cs.LG2010★ 9 cited
Exponential Family Hybrid Semi-Supervised Learning
Arvind Agarwal, Hal Daume
We present an approach to semi-supervised learning based on an exponential family characterization. Our approach generalizes previous work on coupled priors for hybrid generative/d…