Aurélien Lucchi

Orcid: 0000-0001-7015-2710

According to our database1, Aurélien Lucchi authored at least 87 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Cubic regularized subspace Newton for non-convex optimization.
CoRR, 2024

Initial Guessing Bias: How Untrained Networks Favor Some Classes.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

SDEs for Minimax Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Regret-Optimal Federated Transfer Learning for Kernel Regression with Applications in American Option Pricing.
CoRR, 2023

A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Theoretical Analysis of the Learning Dynamics under Class Imbalance.
Proceedings of the International Conference on Machine Learning, 2023

An SDE for Modeling SAM: Theory and Insights.
Proceedings of the International Conference on Machine Learning, 2023

Mastering Spatial Graph Prediction of Road Networks.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Characterizing the Effect of Class Imbalance on the Learning Dynamics.
CoRR, 2022

Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Theoretical Properties of Noise Correlation in Stochastic Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Anticorrelated Noise Injection for Improved Generalization.
Proceedings of the International Conference on Machine Learning, 2022

Phenomenology of Double Descent in Finite-Width Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Generalization Through the Lens of Leave-One-Out Error.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Vanishing Curvature in Randomly Initialized Deep ReLU Networks.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Variational quantum Boltzmann machines.
Quantum Mach. Intell., 2021

The power of quantum neural networks.
Nat. Comput. Sci., 2021

Emulation of Cosmological Mass Maps with Conditional Generative Adversarial Networks.
Frontiers Artif. Intell., 2021

Vanishing Curvature and the Power of Adaptive Methods in Randomly Initialized Deep Networks.
CoRR, 2021

Generative Minimization Networks: Training GANs Without Competition.
CoRR, 2021

On the Second-order Convergence Properties of Random Search Methods.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Symbolic Regression that scales.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Generative Models of Textured 3D Meshes from Real-World Images.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Direct-Search for a Class of Stochastic Min-Max Problems.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Momentum Improves Optimization on Riemannian Manifolds.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Scalable Graph Networks for Particle Simulations.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Theoretical Understanding of Batch-normalization: A Markov Chain Perspective.
CoRR, 2020

Convolutional Generation of Textured 3D Meshes.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Batch normalization provably avoids ranks collapse for randomly initialised deep networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Randomized Block-Diagonal Preconditioning for Parallel Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

An Accelerated DFO Algorithm for Finite-sum Convex Functions.
Proceedings of the 37th International Conference on Machine Learning, 2020

Controlling Style and Semantics in Weakly-Supervised Image Generation.
Proceedings of the Computer Vision - ECCV 2020, 2020

A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
A Stochastic Tensor Method for Non-convex Optimization.
CoRR, 2019

Cosmological N-body simulations: a challenge for scalable generative models.
CoRR, 2019

Ellipsoidal Trust Region Methods and the Marginal Value of Hessian Information for Neural Network Training.
CoRR, 2019

The Role of Memory in Stochastic Optimization.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Shadowing Properties of Optimization Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Continuous-time Models for Stochastic Optimization Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Domain Agnostic Measure for Monitoring and Evaluating GANs.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Topological Map Extraction From Overhead Images.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Exponential convergence rates for Batch Normalization: The power of length-direction decoupling in non-convex optimization.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Local Saddle Point Optimization: A Curvature Exploitation Approach.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
PolyMapper: Extracting City Maps using Polygons.
CoRR, 2018

Evaluating GANs via Duality.
CoRR, 2018

Towards a Theoretical Understanding of Batch Normalization.
CoRR, 2018

Adversarially Robust Training through Structured Gradient Regularization.
CoRR, 2018

A Distributed Second-Order Algorithm You Can Trust.
Proceedings of the 35th International Conference on Machine Learning, 2018

Escaping Saddles with Stochastic Gradients.
Proceedings of the 35th International Conference on Machine Learning, 2018

Semantic Interpolation in Implicit Models.
Proceedings of the 6th International Conference on Learning Representations, 2018

An Online Learning Approach to Generative Adversarial Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Learning Aerial Image Segmentation From Online Maps.
IEEE Trans. Geosci. Remote. Sens., 2017

Flexible Prior Distributions for Deep Generative Models.
CoRR, 2017

Generator Reversal.
CoRR, 2017

Radio frequency interference mitigation using deep convolutional neural networks.
Astron. Comput., 2017

Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification.
Proceedings of the 26th International Conference on World Wide Web, 2017

Stabilizing Training of Generative Adversarial Networks through Regularization.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sub-sampled Cubic Regularization for Non-convex Optimization.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
DynaNewton - Accelerating Newton's Method for Machine Learning.
CoRR, 2016

Bootstrap, Review, Decode: Using Out-of-Domain Textual Data to Improve Image Captioning.
CoRR, 2016

Probabilistic Bag-Of-Hyperlinks Model for Entity Linking.
Proceedings of the 25th International Conference on World Wide Web, 2016

SwissCheese at SemEval-2016 Task 4: Sentiment Classification Using an Ensemble of Convolutional Neural Networks with Distant Supervision.
Proceedings of the 10th International Workshop on Semantic Evaluation, 2016

Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Starting Small - Learning with Adaptive Sample Sizes.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Learning Structured Models for Segmentation of 2-D and 3-D Imagery.
IEEE Trans. Medical Imaging, 2015

A Variance Reduced Stochastic Newton Method.
CoRR, 2015

Neighborhood Watch: Stochastic Gradient Descent with Neighbors.
CoRR, 2015

Variance Reduced Stochastic Gradient Descent with Neighbors.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Exploiting Enclosing Membranes and Contextual Cues for Mitochondria Segmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

2013
Learning Discriminative Features and Structured Models for Segmentation in Microscopy and Natural Images.
PhD thesis, 2013

Flash Scanning Electron Microscopy.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

An Optimal Policy for Target Localization with Application to Electron Microscopy.
Proceedings of the 30th International Conference on Machine Learning, 2013

Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012
Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks With Learned Shape Features.
IEEE Trans. Medical Imaging, 2012

SLIC Superpixels Compared to State-of-the-Art Superpixel Methods.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Efficient Scanning for EM Based Target Localization.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Joint Image and Word Sense Discrimination for Image Retrieval.
Proceedings of the Computer Vision - ECCV 2012, 2012

Structured Image Segmentation Using Kernelized Features.
Proceedings of the Computer Vision - ECCV 2012, 2012

2011
Are spatial and global constraints really necessary for segmentation?
Proceedings of the IEEE International Conference on Computer Vision, 2011

2010
An empirical evaluation of touch and tangible interfaces for tabletop displays.
Proceedings of the 4th International Conference on Tangible and Embedded Interaction 2010, 2010

A Fully Automated Approach to Segmentation of Irregularly Shaped Cellular Structures in EM Images.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010

2009
TinkerSheets: using paper forms to control and visualize tangible simulations.
Proceedings of the 3rd International Conference on Tangible and Embedded Interaction 2009, 2009

Physical space and division of labor around a tabletop tangible simulation.
Proceedings of the 8th International Conference on Computer Supported Collaborative Learning, 2009


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