Simon Lacoste-Julien

Orcid: 0000-0001-6485-6180

According to our database1, Simon Lacoste-Julien authored at least 102 papers between 2005 and 2024.

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

Timeline

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Bibliography

2024
Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies.
CoRR, 2024

2023
A Survey of Self-Supervised and Few-Shot Object Detection.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Weight-Sharing Regularization.
CoRR, 2023

Balancing Act: Constraining Disparate Impact in Sparse Models.
CoRR, 2023

Promoting Exploration in Memory-Augmented Adam using Critical Momenta.
CoRR, 2023

Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection.
CoRR, 2023

PopulAtion Parameter Averaging (PAPA).
CoRR, 2023

Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unlocking Slot Attention by Changing Optimal Transport Costs.
Proceedings of the International Conference on Machine Learning, 2023

Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning.
Proceedings of the International Conference on Machine Learning, 2023

Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?
Proceedings of the International Conference on Machine Learning, 2023

CrossSplit: Mitigating Label Noise Memorization through Data Splitting.
Proceedings of the International Conference on Machine Learning, 2023

2022
SVRG meets AdaGrad: painless variance reduction.
Mach. Learn., 2022

Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information.
INFORMS J. Comput., 2022

Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective.
CoRR, 2022

Partial Disentanglement via Mechanism Sparsity.
CoRR, 2022

Bayesian structure learning with generative flow networks.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Data-Efficient Structured Pruning via Submodular Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Online Adversarial Attacks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

On the Convergence of Continuous Constrained Optimization for Structure Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Convergence Rates for the MAP of an Exponential Family and Stochastic Mirror Descent - an Open Problem.
CoRR, 2021

Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA.
CoRR, 2021

Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Structured Convolutional Kernel Networks for Airline Crew Scheduling.
Proceedings of the 38th International Conference on Machine Learning, 2021

Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets.
Proceedings of the 38th International Conference on Machine Learning, 2021

Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

An Analysis of the Adaptation Speed of Causal Models.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Implicit Regularization via Neural Feature Alignment.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Machine learning in airline crew pairing to construct initial clusters for dynamic constraint aggregation.
EURO J. Transp. Logist., 2020

Geometry-Aware Universal Mirror-Prox.
CoRR, 2020

On the Convergence of Continuous Constrained Optimization for Structure Learning.
CoRR, 2020

Flight-connection Prediction for Airline Crew Scheduling to Construct Initial Clusters for OR Optimizer.
CoRR, 2020

Implicit Regularization in Deep Learning: A View from Function Space.
CoRR, 2020

Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search).
CoRR, 2020

To Each Optimizer a Norm, To Each Norm its Generalization.
CoRR, 2020

Differentiable Causal Discovery from Interventional Data.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adversarial Example Games.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Stochastic Hamiltonian Gradient Methods for Smooth Games.
Proceedings of the 37th International Conference on Machine Learning, 2020

Gradient-Based Neural DAG Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

A Closer Look at the Optimization Landscapes of Generative Adversarial Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

GAIT: A Geometric Approach to Information Theory.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Accelerating Smooth Games by Manipulating Spectral Shapes.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Scattering Networks for Hybrid Representation Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

GEAR: Geometry-Aware Rényi Information.
CoRR, 2019

A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games.
CoRR, 2019

Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks.
CoRR, 2019

Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification.
CoRR, 2019

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Reducing Noise in GAN Training with Variance Reduced Extragradient.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Variational Inequality Perspective on Generative Adversarial Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Negative Momentum for Improved Game Dynamics.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Learning from Narrated Instruction Videos.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods.
J. Mach. Learn. Res., 2018

A Modern Take on the Bias-Variance Tradeoff in Neural Networks.
CoRR, 2018

Predicting Solution Summaries to Integer Linear Programs under Imperfect Information with Machine Learning.
CoRR, 2018

A Variational Inequality Perspective on Generative Adversarial Nets.
CoRR, 2018

A3T: Adversarially Augmented Adversarial Training.
CoRR, 2018

Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Quantifying Learning Guarantees for Convex but Inconsistent Surrogates.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

SEARNN: Training RNNs with global-local losses.
Proceedings of the 6th International Conference on Learning Representations, 2018

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling.
Proceedings of the 6th International Conference on Learning Representations, 2018

Frank-Wolfe Splitting via Augmented Lagrangian Method.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Adversarial Divergences are Good Task Losses for Generative Modeling.
CoRR, 2017

Joint Discovery of Object States and Manipulating Actions.
CoRR, 2017

Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

On Structured Prediction Theory with Calibrated Convex Surrogate Losses.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Closer Look at Memorization in Deep Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Joint Discovery of Object States and Manipulation Actions.
Proceedings of the IEEE International Conference on Computer Vision, 2017

ASAGA: Asynchronous Parallel SAGA.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Frank-Wolfe Algorithms for Saddle Point Problems.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Convergence Rate of Frank-Wolfe for Non-Convex Objectives.
CoRR, 2016

PAC-Bayesian Theory Meets Bayesian Inference.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Beyond CCA: Moment Matching for Multi-View Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Unsupervised Learning from Narrated Instruction Videos.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Rethinking LDA: Moment Matching for Discrete ICA.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

On the Global Linear Convergence of Frank-Wolfe Optimization Variants.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Barrier Frank-Wolfe for Marginal Inference.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 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

On pairwise costs for network flow multi-object tracking.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
On Pairwise Cost for Multi-Object Network Flow Tracking.
CoRR, 2014

SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
SIGMa: simple greedy matching for aligning large knowledge bases.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Block-Coordinate Frank-Wolfe Optimization for Structural SVMs.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method
CoRR, 2012

Stochastic Block-Coordinate Frank-Wolfe Optimization for Structural SVMs
CoRR, 2012

On the Equivalence between Herding and Conditional Gradient Algorithms.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Approximate inference for the loss-calibrated Bayesian.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

2008
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2006
Structured Prediction, Dual Extragradient and Bregman Projections.
J. Mach. Learn. Res., 2006

Word Alignment via Quadratic Assignment.
Proceedings of the Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, 2006

2005
Structured Prediction via the Extragradient Method.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

A Discriminative Matching Approach to Word Alignment.
Proceedings of the HLT/EMNLP 2005, 2005


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