Search Results for author: Moein Falahatgar

Found 7 papers, 0 papers with code

Optimal Sequential Maximization: One Interview is Enough!

no code implementations ICML 2020 Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati

To derive these results we consider a probabilistic setting where several candidates for a position are asked multiple questions with the goal of finding who has the highest probability of answering interview questions correctly.

The Limits of Maxing, Ranking, and Preference Learning

no code implementations ICML 2018 Moein Falahatgar, Ayush Jain, Alon Orlitsky, Venkatadheeraj Pichapati, Vaishakh Ravindrakumar

We present a comprehensive understanding of three important problems in PAC preference learning: maximum selection (maxing), ranking, and estimating all pairwise preference probabilities, in the adaptive setting.

Maxing and Ranking with Few Assumptions

no code implementations NeurIPS 2017 Moein Falahatgar, Yi Hao, Alon Orlitsky, Venkatadheeraj Pichapati, Vaishakh Ravindrakumar

PAC maximum selection (maxing) and ranking of $n$ elements via random pairwise comparisons have diverse applications and have been studied under many models and assumptions.

Maximum Selection and Ranking under Noisy Comparisons

no code implementations ICML 2017 Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh

We consider $(\epsilon,\delta)$-PAC maximum-selection and ranking for general probabilistic models whose comparisons probabilities satisfy strong stochastic transitivity and stochastic triangle inequality.

Faster Algorithms for Testing under Conditional Sampling

no code implementations16 Apr 2015 Moein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapathi, Ananda Theertha Suresh

There has been considerable recent interest in distribution-tests whose run-time and sample requirements are sublinear in the domain-size $k$.

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