
FiDEx: Improving SequencetoSequence Models for Extractive Rationale Generation
Natural language (NL) explanations of model predictions are gaining popu...
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Towards Understanding the Optimal Behaviors of Deep Active Learning Algorithms
Active learning (AL) algorithms may achieve better performance with fewe...
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LowResource Domain Adaptation for Compositional TaskOriented Semantic Parsing
Taskoriented semantic parsing is a critical component of virtual assist...
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Direct Estimation of Difference Between Structural Equation Models in High Dimensions
Discovering causeeffect relationships between variables from observatio...
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Minimax bounds for structured prediction
Structured prediction can be considered as a generalization of many stan...
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Learning MaximumAPosteriori Perturbation Models for Structured Prediction in Polynomial Time
MAP perturbation models have emerged as a powerful framework for inferen...
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Learning linear structural equation models in polynomial time and sample complexity
The problem of learning structural equation models (SEMs) from data is a...
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Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity
Learning the directed acyclic graph (DAG) structure of a Bayesian networ...
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From Behavior to Sparse Graphical Games: Efficient Recovery of Equilibria
In this paper we study the problem of exact recovery of the purestrateg...
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Informationtheoretic limits of Bayesian network structure learning
In this paper, we study the informationtheoretic limits of learning the...
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Asish Ghoshal
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