Search Results for author: Pasha Khosravi

Found 7 papers, 4 papers with code

Generating High Fidelity Synthetic Data via Coreset selection and Entropic Regularization

no code implementations31 Jan 2023 Omead Pooladzandi, Pasha Khosravi, Erik Nijkamp, Baharan Mirzasoleiman

Generative models have the ability to synthesize data points drawn from the data distribution, however, not all generated samples are high quality.

Sales Channel Optimization via Simulations Based on Observational Data with Delayed Rewards: A Case Study at LinkedIn

no code implementations16 Sep 2022 Diana M. Negoescu, Pasha Khosravi, Shadow Zhao, Nanyu Chen, Parvez Ahammad, Humberto Gonzalez

This opens questions regarding not only which decision-making policies would perform best in practice, but also regarding the impact of different data collection protocols on the performance of various policies trained on the data, or the robustness of policy performance with respect to changes in problem characteristics such as action- or reward- specific delays in observing outcomes.

Decision Making

Probabilistic Sufficient Explanations

1 code implementation21 May 2021 Eric Wang, Pasha Khosravi, Guy Van Den Broeck

Understanding the behavior of learned classifiers is an important task, and various black-box explanations, logical reasoning approaches, and model-specific methods have been proposed.

Logical Reasoning

On Tractable Computation of Expected Predictions

1 code implementation NeurIPS 2019 Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van Den Broeck

In this paper, we identify a pair of generative and discriminative models that enables tractable computation of expectations, as well as moments of any order, of the latter with respect to the former in case of regression.

Fairness Imputation +1

What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features

1 code implementation5 Mar 2019 Pasha Khosravi, Yitao Liang, YooJung Choi, Guy Van Den Broeck

While discriminative classifiers often yield strong predictive performance, missing feature values at prediction time can still be a challenge.

Imputation regression

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