
Implicit bias of any algorithm: bounding bias via margin
Consider n points x_1,…,x_n in finitedimensional euclidean space, each ...
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Universal LowerBounds on Classification Error under Adversarial Attacks and Random Corruption
We theoretically analyse the limits of robustness to testtime adversari...
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Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Determinantal point processes (DPPs) have attracted significant attentio...
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Learning disconnected manifolds: a no GANs land
Typical architectures of Generative AdversarialNetworks make use of a un...
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On the Convergence of Approximate and Regularized Policy Iteration Schemes
Algorithms based on the entropy regularized framework, such as Soft Qle...
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Adversarial Robustness via Adversarial LabelSmoothing
We study LabelSmoothing as a means for improving adversarial robustness...
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Distributionally Robust Counterfactual Risk Minimization
This manuscript introduces the idea of using Distributionally Robust Opt...
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Learning Nonsymmetric Determinantal Point Processes
Determinantal point processes (DPPs) have attracted substantial attentio...
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Distributionally Robust Reinforcement Learning
Generalization to unknown/uncertain environments of reinforcement learni...
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Deep Determinantal Point Processes
Determinantal point processes (DPPs) have attracted significant attentio...
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Limitations of adversarial robustness: strong No Free Lunch Theorem
This manuscript presents some new results on adversarial robustness in m...
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Iterative Smoothing Proximal Gradient for Regression with Structured Sparsity
In the context highdimensionnal predictive models, we consider the prob...
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FAASTA: A fast solver for totalvariation regularization of illconditioned problems with application to brain imaging
The total variation (TV) penalty, as many other analysissparsity proble...
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Region segmentation for sparse decompositions: better brain parcellations from rest fMRI
Functional Magnetic Resonance Images acquired during restingstate provi...
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Elvis Dohmatob
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