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Learning with Differentiable Perturbed Optimizers
v1v2 (latest)

Learning with Differentiable Perturbed Optimizers

20 February 2020
Quentin Berthet
Mathieu Blondel
O. Teboul
Marco Cuturi
Jean-Philippe Vert
Francis R. Bach
ArXiv (abs)PDFHTML

Papers citing "Learning with Differentiable Perturbed Optimizers"

50 / 66 papers shown
Decision-focused Sensing and Forecasting for Adaptive and Rapid Flood Response: An Implicit Learning Approach
Decision-focused Sensing and Forecasting for Adaptive and Rapid Flood Response: An Implicit Learning Approach
Qian Sun
Graham Hults
Susu Xu
AI4CE
163
0
0
15 Oct 2025
Scaling Neuro-symbolic Problem Solving: Solver-Free Learning of Constraints and Objectives
Scaling Neuro-symbolic Problem Solving: Solver-Free Learning of Constraints and Objectives
Marianne Defresne
Romain Gambardella
S. Barbe
T. Schiex
250
0
0
28 Aug 2025
Structured Reinforcement Learning for Combinatorial Decision-Making
Structured Reinforcement Learning for Combinatorial Decision-Making
Heiko Hoppe
Léo Baty
Louis Bouvier
Axel Parmentier
Maximilian Schiffer
OffRL
599
6
0
25 May 2025
Learning with Local Search MCMC Layers
Learning with Local Search MCMC Layers
Germain Vivier-Ardisson
Mathieu Blondel
Axel Parmentier
423
1
0
20 May 2025
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach
Rares Cristian
Pavithra Harsha
Georgia Perakis
Brian Quanz
335
1
0
16 May 2025
Sufficient Decision Proxies for Decision-Focused Learning
Sufficient Decision Proxies for Decision-Focused Learning
Noah Schutte
Grigorii Veviurko
Krzysztof Postek
Neil Yorke-Smith
273
0
0
06 May 2025
Decision-aware training of spatiotemporal forecasting models to select a top K subset of sites for intervention
Decision-aware training of spatiotemporal forecasting models to select a top K subset of sites for intervention
Kyle Heuton
F. Samuel Muench
Shikhar Shrestha
Thomas J. Stopka
Michael C. Hughes
OffRL
622
0
0
07 Mar 2025
DistrictNet: Decision-aware learning for geographical districting
DistrictNet: Decision-aware learning for geographical districtingNeural Information Processing Systems (NeurIPS), 2024
Cheikh Ahmed
Alexandre Forel
Axel Parmentier
Thibaut Vidal
344
4
0
11 Dec 2024
Generalizing Stochastic Smoothing for Differentiation and Gradient
  Estimation
Generalizing Stochastic Smoothing for Differentiation and Gradient Estimation
Felix Petersen
Christian Borgelt
Aashwin Mishra
Stefano Ermon
273
4
0
10 Oct 2024
Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems
Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems
Pierre-Cyril Aubin-Frankowski
Yohann de Castro
Axel Parmentier
Alessandro Rudi
OffRL
349
5
0
24 Jul 2024
On The Statistical Representation Properties Of The Perturb-Softmax And
  The Perturb-Argmax Probability Distributions
On The Statistical Representation Properties Of The Perturb-Softmax And The Perturb-Argmax Probability Distributions
Hedda Cohen Indelman
Tamir Hazan
231
0
0
04 Jun 2024
CF-OPT: Counterfactual Explanations for Structured Prediction
CF-OPT: Counterfactual Explanations for Structured Prediction
Germain Vivier-Ardisson
Alexandre Forel
Axel Parmentier
Thibaut Vidal
OffRLCMLBDL
441
3
0
28 May 2024
Exact Solution to Data-Driven Inverse Optimization of MILPs in Finite Time via Gradient-Based Methods
Exact Solution to Data-Driven Inverse Optimization of MILPs in Finite Time via Gradient-Based Methods
Akira Kitaoka
429
1
0
23 May 2024
Transforming a Non-Differentiable Rasterizer into a Differentiable One
  with Stochastic Gradient Estimation
Transforming a Non-Differentiable Rasterizer into a Differentiable One with Stochastic Gradient Estimation
Thomas Deliot
Eric Heitz
Laurent Belcour
294
10
0
15 Apr 2024
CaVE: A Cone-Aligned Approach for Fast Predict-then-optimize with Binary
  Linear Programs
CaVE: A Cone-Aligned Approach for Fast Predict-then-optimize with Binary Linear ProgramsIntegration of AI and OR Techniques in Constraint Programming (CPAIOR), 2023
Bo Tang
Elias Boutros Khalil
289
5
0
12 Dec 2023
Everybody Needs a Little HELP: Explaining Graphs via Hierarchical
  Concepts
Everybody Needs a Little HELP: Explaining Graphs via Hierarchical Concepts
Jonas Jürß
Lucie Charlotte Magister
Pietro Barbiero
Pietro Lio
Nikola Simidjievski
486
1
0
25 Nov 2023
Rethinking and Benchmarking Predict-then-Optimize Paradigm for
  Combinatorial Optimization Problems
Rethinking and Benchmarking Predict-then-Optimize Paradigm for Combinatorial Optimization ProblemsNeural Information Processing Systems (NeurIPS), 2023
Haoyu Geng
Hang Ruan
Runzhong Wang
Yang Li
Yang Wang
Lei Chen
Junchi Yan
362
0
0
13 Nov 2023
Robust Losses for Decision-Focused Learning
Robust Losses for Decision-Focused LearningInternational Joint Conference on Artificial Intelligence (IJCAI), 2023
Noah Schutte
Krzysztof Postek
Neil Yorke-Smith
338
7
0
06 Oct 2023
You Shall Pass: Dealing with the Zero-Gradient Problem in Predict and
  Optimize for Convex Optimization
You Shall Pass: Dealing with the Zero-Gradient Problem in Predict and Optimize for Convex Optimization
Grigorii Veviurko
Wendelin Bohmer
Mathijs de Weerdt
326
3
0
30 Jul 2023
Decision-Focused Learning: Foundations, State of the Art, Benchmark and
  Future Opportunities
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future OpportunitiesJournal of Artificial Intelligence Research (JAIR), 2023
Jayanta Mandi
James Kotary
Senne Berden
Maxime Mulamba
Víctor Bucarey
Tias Guns
Ferdinando Fioretto
AI4CE
545
150
0
25 Jul 2023
A Survey of Contextual Optimization Methods for Decision Making under
  Uncertainty
A Survey of Contextual Optimization Methods for Decision Making under UncertaintyEuropean Journal of Operational Research (EJOR), 2023
Utsav Sadana
A. Chenreddy
Erick Delage
Alexandre Forel
Emma Frejinger
Thibaut Vidal
AI4CE
430
170
0
17 Jun 2023
Implicit Bilevel Optimization: Differentiating through Bilevel
  Optimization Programming
Implicit Bilevel Optimization: Differentiating through Bilevel Optimization ProgrammingAAAI Conference on Artificial Intelligence (AAAI), 2023
Francesco Alesiani
250
7
0
28 Feb 2023
Sketch In, Sketch Out: Accelerating both Learning and Inference for
  Structured Prediction with Kernels
Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with KernelsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
T. Ahmad
Luc Brogat-Motte
Pierre Laforgue
Florence dÁlché-Buc
BDL
389
6
0
20 Feb 2023
Learning to Solve Integer Linear Programs with Davis-Yin Splitting
Learning to Solve Integer Linear Programs with Davis-Yin Splitting
Daniel McKenzie
Samy Wu Fung
Howard Heaton
302
11
0
31 Jan 2023
Deep Differentiable Logic Gate Networks
Deep Differentiable Logic Gate NetworksNeural Information Processing Systems (NeurIPS), 2022
Felix Petersen
Christian Borgelt
Hilde Kuehne
Oliver Deussen
AI4CE
253
76
0
15 Oct 2022
Learning with Combinatorial Optimization Layers: a Probabilistic
  Approach
Learning with Combinatorial Optimization Layers: a Probabilistic Approach
Guillaume Dalle
Léo Baty
Louis Bouvier
Axel Parmentier
AI4CE
366
46
0
27 Jul 2022
PyEPO: A PyTorch-based End-to-End Predict-then-Optimize Library for
  Linear and Integer Programming
PyEPO: A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer ProgrammingMathematical Programming Computation (MPC), 2022
Bo Tang
Elias Boutros Khalil
258
50
0
28 Jun 2022
Differentiable Top-k Classification Learning
Differentiable Top-k Classification LearningInternational Conference on Machine Learning (ICML), 2022
Felix Petersen
Hilde Kuehne
Christian Borgelt
Oliver Deussen
342
45
0
15 Jun 2022
Backpropagation through Combinatorial Algorithms: Identity with
  Projection Works
Backpropagation through Combinatorial Algorithms: Identity with Projection WorksInternational Conference on Learning Representations (ICLR), 2022
Subham S. Sahoo
Anselm Paulus
Marin Vlastelica
Vít Musil
Volodymyr Kuleshov
Georg Martius
428
33
0
30 May 2022
GenDR: A Generalized Differentiable Renderer
GenDR: A Generalized Differentiable RendererComputer Vision and Pattern Recognition (CVPR), 2022
Felix Petersen
Bastian Goldluecke
Christian Borgelt
Oliver Deussen
206
20
0
29 Apr 2022
Finding Structure and Causality in Linear Programs
Finding Structure and Causality in Linear Programs
Matej Zečević
Florian Peter Busch
Devendra Singh Dhami
Kristian Kersting
CML
158
0
0
29 Mar 2022
ScoreNet: Learning Non-Uniform Attention and Augmentation for
  Transformer-Based Histopathological Image Classification
ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image ClassificationIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022
Thomas Stegmüller
Behzad Bozorgtabar
A. Spahr
Jean-Philippe Thiran
ViTMedIm
373
47
0
15 Feb 2022
Stochastic smoothing of the top-K calibrated hinge loss for deep
  imbalanced classification
Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classificationInternational Conference on Machine Learning (ICML), 2022
Camille Garcin
Maximilien Servajean
Alexis Joly
Joseph Salmon
285
13
0
04 Feb 2022
Efficient Video Transformers with Spatial-Temporal Token Selection
Efficient Video Transformers with Spatial-Temporal Token Selection
Junke Wang
Xitong Yang
Hengduo Li
Li Liu
Zuxuan Wu
Yu-Gang Jiang
ViT
239
89
0
23 Nov 2021
A Surrogate Objective Framework for Prediction+Optimization with Soft
  Constraints
A Surrogate Objective Framework for Prediction+Optimization with Soft Constraints
Kai Yan
Jie Yan
Chuan Luo
Liting Chen
Qingwei Lin
Dongmei Zhang
214
4
0
22 Nov 2021
Integrated Conditional Estimation-Optimization
Integrated Conditional Estimation-Optimization
Sirui Chen
Paul Grigas
Zuo‐Jun Max Shen
CML
377
33
0
24 Oct 2021
Differentiable Rendering with Perturbed Optimizers
Differentiable Rendering with Perturbed Optimizers
Quentin Le Lidec
Ivan Laptev
Cordelia Schmid
Justin Carpentier
233
17
0
18 Oct 2021
Learning with Algorithmic Supervision via Continuous Relaxations
Learning with Algorithmic Supervision via Continuous RelaxationsNeural Information Processing Systems (NeurIPS), 2021
Felix Petersen
Christian Borgelt
Hilde Kuehne
Oliver Deussen
CLL
254
33
0
11 Oct 2021
Sparse MoEs meet Efficient Ensembles
Sparse MoEs meet Efficient Ensembles
J. Allingham
F. Wenzel
Zelda E. Mariet
Basil Mustafa
J. Puigcerver
...
Balaji Lakshminarayanan
Jasper Snoek
Dustin Tran
Carlos Riquelme Ruiz
Rodolphe Jenatton
MoE
422
23
0
07 Oct 2021
Differentiable Equilibrium Computation with Decision Diagrams for
  Stackelberg Models of Combinatorial Congestion Games
Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games
Shinsaku Sakaue
Kengo Nakamura
226
4
0
05 Oct 2021
Differentiable Spline Approximations
Differentiable Spline Approximations
Minsu Cho
Aditya Balu
Ameya Joshi
Anjana Prasad
Biswajit Khara
Soumik Sarkar
Baskar Ganapathysubramanian
A. Krishnamurthy
Chinmay Hegde
197
6
0
04 Oct 2021
A Review of the Gumbel-max Trick and its Extensions for Discrete
  Stochasticity in Machine Learning
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning
Iris A. M. Huijben
W. Kool
Max B. Paulus
Ruud J. G. van Sloun
440
134
0
04 Oct 2021
Sparse Communication via Mixed Distributions
Sparse Communication via Mixed DistributionsInternational Conference on Learning Representations (ICLR), 2021
António Farinhas
Wilker Aziz
Vlad Niculae
André F. T. Martins
226
3
0
05 Aug 2021
Unsupervised Resource Allocation with Graph Neural Networks
Unsupervised Resource Allocation with Graph Neural Networks
M. Cranmer
Peter Melchior
Brian D. Nord
237
15
0
17 Jun 2021
Combinatorial Optimization for Panoptic Segmentation: A Fully
  Differentiable Approach
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable ApproachNeural Information Processing Systems (NeurIPS), 2021
Ahmed Abbas
Paul Swoboda
465
16
0
06 Jun 2021
Structural Causal Models Reveal Confounder Bias in Linear Program
  Modelling
Structural Causal Models Reveal Confounder Bias in Linear Program ModellingMachine-mediated learning (ML), 2021
Matej Zečević
Devendra Singh Dhami
Kristian Kersting
AAML
220
1
0
26 May 2021
CombOptNet: Fit the Right NP-Hard Problem by Learning Integer
  Programming Constraints
CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming ConstraintsInternational Conference on Machine Learning (ICML), 2021
Anselm Paulus
Michal Rolínek
Vít Musil
Brandon Amos
Georg Martius
371
72
0
05 May 2021
Neural Weighted A*: Learning Graph Costs and Heuristics with
  Differentiable Anytime A*
Neural Weighted A*: Learning Graph Costs and Heuristics with Differentiable Anytime A*International Conference on Machine Learning, Optimization, and Data Science (MOD), 2021
Alberto Archetti
Marco Cannici
Matteo Matteucci
292
8
0
04 May 2021
Differentiable Patch Selection for Image Recognition
Differentiable Patch Selection for Image RecognitionComputer Vision and Pattern Recognition (CVPR), 2021
Jean-Baptiste Cordonnier
Aravindh Mahendran
Alexey Dosovitskiy
Dirk Weissenborn
Jakob Uszkoreit
Thomas Unterthiner
251
117
0
07 Apr 2021
Reconciling the Discrete-Continuous Divide: Towards a Mathematical
  Theory of Sparse Communication
Reconciling the Discrete-Continuous Divide: Towards a Mathematical Theory of Sparse Communication
André F. T. Martins
330
1
0
01 Apr 2021
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