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07/10/2023
Generalization Error of First-Order Methods for Statistical Learning with Generic Oracles
In this paper, we provide a novel framework for the analysis of generali...
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04/21/2023
Black-box Acceleration of Las Vegas Algorithms and Algorithmic Reverse Jensen's Inequalities
Let 𝒜 be a Las Vegas algorithm, i.e. an algorithm whose running time T i...
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01/19/2023
Convergence beyond the over-parameterized regime using Rayleigh quotients
In this paper, we present a new strategy to prove the convergence of dee...
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06/02/2021
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
This paper provides a non-asymptotic analysis of linear stochastic appro...
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03/08/2021
Lipschitz Normalization for Self-Attention Layers with Application to Graph Neural Networks
Attention based neural networks are state of the art in a large range of...
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02/17/2021
Improving Hierarchical Adversarial Robustness of Deep Neural Networks
Do all adversarial examples have the same consequences? An autonomous dr...
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02/17/2021
Ego-based Entropy Measures for Structural Representations on Graphs
Machine learning on graph-structured data has attracted high research in...
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03/01/2020
Ego-based Entropy Measures for Structural Representations
In complex networks, nodes that share similar structural characteristics...
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12/12/2019
Coloring graph neural networks for node disambiguation
In this paper, we show that a simple coloring scheme can improve, both t...
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10/11/2019
Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning
We investigate the theoretical limits of pipeline parallel learning of d...
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05/28/2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation
Deep neural networks are notorious for being sensitive to small well-cho...
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05/25/2018
KONG: Kernels for ordered-neighborhood graphs
We present novel graph kernels for graphs with node and edge labels that...
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09/15/2017
A Spectral Method for Activity Shaping in Continuous-Time Information Cascades
Information Cascades Model captures dynamical properties of user activit...
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02/28/2017
Optimal algorithms for smooth and strongly convex distributed optimization in networks
In this paper, we determine the optimal convergence rates for strongly c...
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02/26/2016