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06/30/2023
Global Optimality in Bivariate Gradient-based DAG Learning
Recently, a new class of non-convex optimization problems motivated by t...
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06/30/2023
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models
Structural causal models (SCMs) are widely used in various disciplines t...
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05/26/2023
Optimizing NOTEARS Objectives via Topological Swaps
Recently, an intriguing class of non-convex optimization problems has em...
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09/16/2022
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization
The combinatorial problem of learning directed acyclic graphs (DAGs) fro...
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02/17/2021
On the Fundamental Limits of Exact Inference in Structured Prediction
Inference is a main task in structured prediction and it is naturally mo...
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02/16/2021
A Thorough View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy
Performing inference in graphs is a common task within several machine l...
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02/16/2021
Inverse Reinforcement Learning in the Continuous Setting with Formal Guarantees
Inverse Reinforcement Learning (IRL) is the problem of finding a reward ...
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07/01/2020
Fundamental Limits of Adversarial Learning
Robustness of machine learning methods is essential for modern practical...
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07/01/2020
Fairness constraints can help exact inference in structured prediction
Many inference problems in structured prediction can be modeled as maxim...
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06/02/2019
Exact inference in structured prediction
Structured prediction can be thought of as a simultaneous prediction of ...
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06/02/2019
Minimax bounds for structured prediction
Structured prediction can be considered as a generalization of many stan...
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05/23/2018
Learning latent variable structured prediction models with Gaussian perturbations
The standard margin-based structured prediction commonly uses a maximum ...
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06/02/2017