Search Results for author: Miroslav Dudik

Found 9 papers, 7 papers with code

A structured regression approach for evaluating model performance across intersectional subgroups

no code implementations26 Jan 2024 Christine Herlihy, Kimberly Truong, Alexandra Chouldechova, Miroslav Dudik

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.

Fairness regression

Optimal and Adaptive Off-policy Evaluation in Contextual Bandits

2 code implementations ICML 2017 Yu-Xiang Wang, Alekh Agarwal, Miroslav Dudik

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.

Multi-Armed Bandits Off-policy evaluation

Contextual Semibandits via Supervised Learning Oracles

1 code implementation NeurIPS 2016 Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudik

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.

Decision Making Learning-To-Rank

Para-active learning

no code implementations30 Oct 2013 Alekh Agarwal, Leon Bottou, Miroslav Dudik, John Langford

We leverage the same observation to build a generic strategy for parallelizing learning algorithms.

Active Learning

A Reliable Effective Terascale Linear Learning System

2 code implementations19 Oct 2011 Alekh Agarwal, Olivier Chapelle, Miroslav Dudik, John Langford

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

1 code implementation23 Mar 2011 Miroslav Dudik, John Langford, Lihong Li

The key challenge is that the past data typically does not faithfully represent proportions of actions taken by a new policy.

Decision Making Multi-Armed Bandits

Faster solutions of the inverse pairwise Ising problem

1 code implementation14 Dec 2007 Tamara Broderick, Miroslav Dudik, Gasper Tkacik, Robert E. Schapire, William Bialek

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.

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