Publications [#340078] of Lawrence Carin

Papers Published

1. Tao, C; Chen, L; Zhang, R; Henao, R; Carin, L, Variational inference and model selection with generalized evidence bounds, 35th International Conference on Machine Learning, ICML 2018, vol. 2 (January, 2018), pp. 1419-1435, ISBN 9781510867963
   (last updated on 2024/12/31)

   Abstract:
   Recent advances on the scalability and flexibility of variational inference have made it successful at unravelling hidden patterns in complex data. In this work we propose a new variational bound formulation, yielding an estimator that extends beyond the conventional variational bound. It naturally subsumes the importance-weighted and Renyi bounds as special cases, and it is provably sharper than these counterparts. We also present an improved estimator for variational learning, and advocate a novel high signal-to-variance ratio update rule for the variational parameters. We discuss model-selection issues associated with existing evidence-lower-bound-based variational inference procedures, and show how to leverage the flexibility of our new formulation to address them. Empirical evidence is provided to validate our claims.