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The Limited Multi-Label Projection Layer
v1v2v3 (latest)

The Limited Multi-Label Projection Layer

20 June 2019
Brandon Amos
V. Koltun
J. Zico Kolter
ArXiv (abs)PDFHTML

Papers citing "The Limited Multi-Label Projection Layer"

23 / 23 papers shown
Prediction Loss Guided Decision-Focused Learning
Prediction Loss Guided Decision-Focused Learning
Haeun Jeon
Hyunglip Bae
Chanyeong Kim
Yongjae Lee
Woo Chang Kim
66
0
0
10 Sep 2025
Preference-Optimized Pareto Set Learning for Blackbox Optimization
Preference-Optimized Pareto Set Learning for Blackbox Optimization
Zhang Haishan
Chen Liang
Koji Tsuda
224
1
0
19 Aug 2024
LPGD: A General Framework for Backpropagation through Embedded
  Optimization Layers
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers
Anselm Paulus
Georg Martius
Vít Musil
AI4CE
279
4
0
08 Jul 2024
Efficient Public Health Intervention Planning Using Decomposition-Based
  Decision-Focused Learning
Efficient Public Health Intervention Planning Using Decomposition-Based Decision-Focused LearningAdaptive Agents and Multi-Agent Systems (AAMAS), 2024
Sanket Shah
A. Suggala
Milind Tambe
Aparna Taneja
188
0
0
08 Mar 2024
End-to-End Learning for Fair Multiobjective Optimization Under
  Uncertainty
End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty
M. H. Dinh
James Kotary
Ferdinando Fioretto
202
2
0
12 Feb 2024
Analyzing and Enhancing the Backward-Pass Convergence of Unrolled
  Optimization
Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization
James Kotary
Jacob K Christopher
M. H. Dinh
Ferdinando Fioretto
157
0
0
28 Dec 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
464
130
0
25 Jul 2023
Adaptive Experimentation at Scale: A Computational Framework for
  Flexible Batches
Adaptive Experimentation at Scale: A Computational Framework for Flexible Batches
Ethan Che
Hongseok Namkoong
OffRL
367
3
0
21 Mar 2023
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective
Fast, Differentiable and Sparse Top-k: a Convex Analysis PerspectiveInternational Conference on Machine Learning (ICML), 2023
Michael E. Sander
J. Puigcerver
Josip Djolonga
Gabriel Peyré
Mathieu Blondel
469
30
0
02 Feb 2023
Backpropagation of Unrolled Solvers with Folded Optimization
Backpropagation of Unrolled Solvers with Folded OptimizationInternational Joint Conference on Artificial Intelligence (IJCAI), 2023
James Kotary
M. H. Dinh
Ferdinando Fioretto
255
18
0
28 Jan 2023
Rank-based Decomposable Losses in Machine Learning: A Survey
Rank-based Decomposable Losses in Machine Learning: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Shu Hu
Xin Wang
Siwei Lyu
332
37
0
18 Jul 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
384
28
0
30 May 2022
Decision-Focused Learning without Differentiable Optimization: Learning
  Locally Optimized Decision Losses
Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses
Sanket Shah
Kai Wang
Bryan Wilder
Andrew Perrault
Milind Tambe
OffRL
222
15
0
30 Mar 2022
ZippyPoint: Fast Interest Point Detection, Description, and Matching
  through Mixed Precision Discretization
ZippyPoint: Fast Interest Point Detection, Description, and Matching through Mixed Precision Discretization
Menelaos Kanakis
S. Maurer
Matteo Spallanzani
Ajad Chhatkuli
Luc Van Gool
3DPC
378
19
0
07 Mar 2022
Tutorial on amortized optimization
Tutorial on amortized optimization
Brandon Amos
OffRL
809
76
0
01 Feb 2022
DiPS: Differentiable Policy for Sketching in Recommender Systems
DiPS: Differentiable Policy for Sketching in Recommender Systems
Aritra Ghosh
Saayan Mitra
Andrew Lan
BDLOffRL
113
3
0
08 Dec 2021
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and
  Beyond
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and BeyondNeural Information Processing Systems (NeurIPS), 2021
Đ.Khuê Lê-Huu
Alahari Karteek
268
13
0
27 Oct 2021
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for
  End-to-End Learning and Control
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-End Learning and Control
Ioannis Exarchos
M. Pereira
Ziyi Wang
Evangelos A. Theodorou
253
4
0
22 Jun 2020
Gradient Estimation with Stochastic Softmax Tricks
Gradient Estimation with Stochastic Softmax TricksNeural Information Processing Systems (NeurIPS), 2020
Max B. Paulus
Dami Choi
Daniel Tarlow
Andreas Krause
Chris J. Maddison
BDL
328
94
0
15 Jun 2020
Learning with Differentiable Perturbed Optimizers
Learning with Differentiable Perturbed Optimizers
Quentin Berthet
Mathieu Blondel
O. Teboul
Marco Cuturi
Jean-Philippe Vert
Francis R. Bach
291
117
0
20 Feb 2020
Differentiable Convex Optimization Layers
Differentiable Convex Optimization LayersNeural Information Processing Systems (NeurIPS), 2019
Akshay Agrawal
Brandon Amos
Shane T. Barratt
Stephen P. Boyd
Steven Diamond
Zico Kolter
265
765
0
28 Oct 2019
Structured Prediction with Projection Oracles
Structured Prediction with Projection OraclesNeural Information Processing Systems (NeurIPS), 2019
Mathieu Blondel
360
35
0
24 Oct 2019
The Differentiable Cross-Entropy Method
The Differentiable Cross-Entropy MethodInternational Conference on Machine Learning (ICML), 2019
Brandon Amos
Denis Yarats
376
58
0
27 Sep 2019
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