Search Results for author:
Found 9 papers, 7 papers with code
A structured regression approach for evaluating model performance across intersectional subgroups
Disaggregated evaluation is a central task in AI fairness assessment, with the goal to measure an AI system's performance across different subgroups defined by combinations of demographic or other sensitive attributes.
Constrained episodic reinforcement learning in concave-convex and knapsack settings
We propose an algorithm for tabular episodic reinforcement learning with constraints.
Reinforcement Learning with Convex Constraints
In standard reinforcement learning (RL), a learning agent seeks to optimize the overall reward.
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
We study the off-policy evaluation problem---estimating the value of a target policy using data collected by another policy---under the contextual bandit model.
Contextual Semibandits via Supervised Learning Oracles
We study an online decision making problem where on each round a learner chooses a list of items based on some side information, receives a scalar feedback value for each individual item, and a reward that is linearly related to this feedback.
Para-active learning
We leverage the same observation to build a generic strategy for parallelizing learning algorithms.
A Reliable Effective Terascale Linear Learning System
We present a system and a set of techniques for learning linear predictors with convex losses on terascale datasets, with trillions of features, {The number of features here refers to the number of non-zero entries in the data matrix.}
Doubly Robust Policy Evaluation and Learning
The key challenge is that the past data typically does not faithfully represent proportions of actions taken by a new policy.
Faster solutions of the inverse pairwise Ising problem
Recent work has shown that probabilistic models based on pairwise interactions-in the simplest case, the Ising model-provide surprisingly accurate descriptions of experiments on real biological networks ranging from neurons to genes.
