research
∙
02/04/2022
Distribution Embedding Networks for Meta-Learning with Heterogeneous Covariate Spaces
We propose Distribution Embedding Networks (DEN) for classification with...
share
research
∙
02/18/2021
Optimizing Black-box Metrics with Iterative Example Weighting
We consider learning to optimize a classification metric defined by a bl...
research
∙
02/20/2020
Optimizing Black-box Metrics with Adaptive Surrogates
We address the problem of training models with black-box and hard-to-opt...
research
∙
06/28/2018
Proxy Fairness
We consider the problem of improving fairness when one lacks access to a...
research
∙
05/27/2018
Metric-Optimized Example Weights
Real-world machine learning applications often have complex test metrics...
research
∙
01/16/2014
Non-Deterministic Policies in Markovian Decision Processes
Markovian processes have long been used to model stochastic environments...
research
∙
12/01/2013
Efficient Learning and Planning with Compressed Predictive States
Predictive state representations (PSRs) offer an expressive framework fo...
research
∙
07/23/2012
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces
We address the problem of automatic generation of features for value fun...
research
∙
02/14/2012