Reviews: Variational Bayesian Decision-making for Continuous Utilities
–Neural Information Processing Systems
Originality: The paper builds on ideas developed by Lacoste-Julien et al. (2011) that were introduced to bridge Bayesian decision theory with approximate inference in a meaningful and useful way. The paper takes these ideas and makes them applicable in continuously-valued settings so long as the losses are bounded. For inference, it uses a variation of'black box' type variational inference schemes. Quality: The paper makes an interesting contribution. However, it is undesirable that the losses must be bounded.
Neural Information Processing Systems
Jan-24-2025, 00:28:25 GMT
- Technology: