Simon Lacoste-Julien

According to our database1, Simon Lacoste-Julien authored at least 61 papers between 2005 and 2018.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

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

Quantifying Learning Guarantees for Convex but Inconsistent Surrogates.
CoRR, 2018

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

Scattering Networks for Hybrid Representation Learning.
CoRR, 2018

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

Negative Momentum for Improved Game Dynamics.
CoRR, 2018

Frank-Wolfe Splitting via Augmented Lagrangian Method.
CoRR, 2018

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

A3T: Adversarially Augmented Adversarial Training.
CoRR, 2018

Improved asynchronous parallel optimization analysis for stochastic incremental methods.
CoRR, 2018

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

2017
Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields.
CoRR, 2017

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

Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization.
CoRR, 2017

On Structured Prediction Theory with Calibrated Convex Surrogate Losses.
CoRR, 2017

SEARNN: Training RNNs with Global-Local Losses.
CoRR, 2017

A Closer Look at Memorization in Deep Networks.
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
Beyond CCA: Moment Matching for Multi-View Models.
CoRR, 2016

Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs.
CoRR, 2016

Asaga: Asynchronous Parallel Saga.
CoRR, 2016

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

Frank-Wolfe Algorithms for Saddle Point Problems.
CoRR, 2016

PAC-Bayesian Theory Meets Bayesian Inference.
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.
CoRR, 2015

Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering.
CoRR, 2015

On the Global Linear Convergence of Frank-Wolfe Optimization Variants.
CoRR, 2015

Barrier Frank-Wolfe for Marginal Inference.
CoRR, 2015

Learning from narrated instruction videos.
CoRR, 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
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives.
CoRR, 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

SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases
CoRR, 2012

On the Equivalence between Herding and Conditional Gradient Algorithms
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.
Journal of Machine Learning Research, 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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