Maruan Al-Shedivat

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Carnegie Mellon University

Ph.D. student in Machine Learning at Carnegie Mellon University

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∙ 09/10/2021

Knowledge-Aware Meta-learning for Low-Resource Text Classification

Meta-learning has achieved great success in leveraging the historical le...

Huaxiu Yao, et al. ∙

∙ 01/30/2021

On Data Efficiency of Meta-learning

Meta-learning has enabled learning statistical models that can be quickl...

Maruan Al-Shedivat, et al. ∙

∙ 10/11/2020

Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms

Federated learning is typically approached as an optimization problem, w...

Maruan Al-Shedivat, et al. ∙

∙ 04/07/2020

Learning from Imperfect Annotations

Many machine learning systems today are trained on large amounts of huma...

Emmanouil Antonios Platanios, et al. ∙

∙ 05/31/2019

Regularizing Black-box Models for Improved Interpretability (HILL 2019 Version)

Most of the work on interpretable machine learning has focused on design...

Gregory Plumb, et al. ∙

∙ 04/04/2019

Consistency by Agreement in Zero-shot Neural Machine Translation

Generalization and reliability of multilingual translation often highly ...

Maruan Al-Shedivat, et al. ∙

∙ 02/18/2019

Regularizing Black-box Models for Improved Interpretability

Most work on interpretability in machine learning has focused on designi...

Gregory Plumb, et al. ∙

∙ 11/16/2018

On the Complexity of Exploration in Goal-Driven Navigation

Building agents that can explore their environments intelligently is a c...

Maruan Al-Shedivat, et al. ∙

∙ 06/17/2018

Learning Policy Representations in Multiagent Systems

Modeling agent behavior is central to understanding the emergence of com...

Aditya Grover, et al. ∙

∙ 02/14/2018

DiCE: The Infinitely Differentiable Monte-Carlo Estimator

The score function estimator is widely used for estimating gradients of ...

Jakob Foerster, et al. ∙

∙ 01/30/2018

Personalized Survival Prediction with Contextual Explanation Networks

Accurate and transparent prediction of cancer survival times on the leve...

Maruan Al-Shedivat, et al. ∙

∙ 01/30/2018

The Intriguing Properties of Model Explanations

Linear approximations to the decision boundary of a complex model have b...

Maruan Al-Shedivat, et al. ∙

∙ 10/10/2017

Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments

Ability to continuously learn and adapt from limited experience in nonst...

Maruan Al-Shedivat, et al. ∙

∙ 09/13/2017

Learning with Opponent-Learning Awareness

Multi-agent settings are quickly gathering importance in machine learnin...

Jakob N. Foerster, et al. ∙

∙ 05/29/2017

Contextual Explanation Networks

We introduce contextual explanation networks (CENs)---a class of models ...

Maruan Al-Shedivat, et al. ∙

∙ 10/27/2016

Learning Scalable Deep Kernels with Recurrent Structure

Many applications in speech, robotics, finance, and biology deal with se...

Maruan Al-Shedivat, et al. ∙

∙ 09/21/2016

Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices

Recently, there has been a surge of interest in using spectral methods f...

Kirthevasan Kandasamy, et al. ∙

∙ 11/14/2015

Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines

Recent studies have shown that synaptic unreliability is a robust and su...

Emre O. Neftci, et al. ∙

∙ 12/23/2014

Learning Non-deterministic Representations with Energy-based Ensembles

The goal of a generative model is to capture the distribution underlying...

Maruan Al-Shedivat, et al. ∙