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Learning with Fenchel-Young Losses

8 January 2019

Mathieu Blondel

André F. T. Martins

Vlad Niculae

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Papers citing "Learning with Fenchel-Young Losses"

43 / 43 papers shown

Title
Box-Constrained Softmax Function and Its Application for Post-Hoc Calibration Kyohei Atarashi S. Oyama Hiromi Arai H. Kashima 120 0 0 12 Jun 2025
Bregman Conditional Random Fields: Sequence Labeling with Parallelizable Inference Algorithms Caio Corro Mathieu Lacroix Joseph Le Roux 20 0 0 31 May 2025
Structured Reinforcement Learning for Combinatorial Decision-Making Heiko Hoppe Léo Baty Louis Bouvier Axel Parmentier Maximilian Schiffer OffRL 107 1 0 25 May 2025
Primal-dual algorithm for contextual stochastic combinatorial optimization Louis Bouvier Thibault Prunet Vincent Leclère Axel Parmentier 70 1 0 07 May 2025
Bandit and Delayed Feedback in Online Structured Prediction Yuki Shibukawa Taira Tsuchiya Shinsaku Sakaue Kenji Yamanishi OffRL 102 0 0 26 Feb 2025
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel $-$ Young Loss Perspective and Gap-Dependent Regret Analysis Shinsaku Sakaue Han Bao Taira Tsuchiya 199 2 0 23 Jan 2025
Soft Condorcet Optimization for Ranking of General Agents Marc Lanctot Kate Larson Michael Kaisers Quentin Berthet I. Gemp Manfred Diaz Roberto-Rafael Maura-Rivero Yoram Bachrach Anna Koop Doina Precup 268 0 0 31 Oct 2024
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers Anselm Paulus Georg Martius Vít Musil AI4CE 112 1 0 08 Jul 2024
How to Boost Any Loss Function Richard Nock Yishay Mansour 62 0 0 02 Jul 2024
Building a stable classifier with the inflated argmax Jake A. Soloff Rina Foygel Barber Rebecca Willett 327 3 0 22 May 2024
Trading off Consistency and Dimensionality of Convex Surrogates for the Mode Enrique Nueve Bo Waggoner Dhamma Kimpara Jessie Finocchiaro 91 1 0 16 Feb 2024
On the Robustness of Decision-Focused Learning Yehya Farhat 75 0 0 28 Nov 2023
When Does Optimizing a Proper Loss Yield Calibration? Jarosław Błasiok Parikshit Gopalan Lunjia Hu Preetum Nakkiran 91 28 0 30 May 2023
Differentiable Clustering with Perturbed Spanning Forests Lawrence Stewart Francis R. Bach Felipe Llinares-López Quentin Berthet 99 11 0 25 May 2023
Loss Minimization Yields Multicalibration for Large Neural Networks Jarosław Błasiok Parikshit Gopalan Lunjia Hu Adam Tauman Kalai Preetum Nakkiran FaML UQCV 93 13 0 19 Apr 2023
A Statistical Learning Take on the Concordance Index for Survival Analysis Alex Nowak-Vila K. Elgui Geneviève Robin 133 1 0 23 Feb 2023
Maximum Optimality Margin: A Unified Approach for Contextual Linear Programming and Inverse Linear Programming Chunlin Sun Shang Liu Xiaocheng Li 96 10 0 26 Jan 2023
On the inconsistency of separable losses for structured prediction Caio Corro 46 3 0 25 Jan 2023
SIMPLE: A Gradient Estimator for $k$ -Subset Sampling Kareem Ahmed Zhe Zeng Mathias Niepert Guy Van den Broeck BDL 136 27 0 04 Oct 2022
Learning with Combinatorial Optimization Layers: a Probabilistic Approach Guillaume Dalle Léo Baty Louis Bouvier Axel Parmentier AI4CE 74 36 0 27 Jul 2022
Rank-based Decomposable Losses in Machine Learning: A Survey Shu Hu Xin Wang Siwei Lyu 100 32 0 18 Jul 2022
Bregman Proximal Langevin Monte Carlo via Bregman--Moreau Envelopes Tim Tsz-Kit Lau Han Liu 127 7 0 10 Jul 2022
PyEPO: A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer Programming Bo Tang Elias Boutros Khalil 87 33 0 28 Jun 2022
Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data Shohreh Deldari Hao Xue Aaqib Saeed Jiayuan He Daniel V. Smith Flora D. Salim AI4TS 75 37 0 06 Jun 2022
Contrasting quadratic assignments for set-based representation learning A. Moskalev Ivan Sosnovik Volker Fischer A. Smeulders SSL 97 9 0 31 May 2022
Learning Energy Networks with Generalized Fenchel-Young Losses Mathieu Blondel Felipe Llinares-López Robert Dadashi Léonard Hussenot Matthieu Geist 95 7 0 19 May 2022
Tutorial on amortized optimization Brandon Amos OffRL 166 48 0 01 Feb 2022
Sparse Communication via Mixed Distributions António Farinhas Wilker Aziz Vlad Niculae André F. T. Martins 61 3 0 05 Aug 2021
Multimodal Continuous Visual Attention Mechanisms António Farinhas André F. T. Martins P. Aguiar 59 7 0 07 Apr 2021
Reconciling the Discrete-Continuous Divide: Towards a Mathematical Theory of Sparse Communication André F. T. Martins 67 1 0 01 Apr 2021
Self-Supervised Learning of Audio Representations from Permutations with Differentiable Ranking Andrew N. Carr Quentin Berthet Mathieu Blondel O. Teboul Neil Zeghidour SSL 75 25 0 17 Mar 2021
Lower-Bounded Proper Losses for Weakly Supervised Classification Shuhei M. Yoshida Takashi Takenouchi Masashi Sugiyama 25 2 0 04 Mar 2021
Moreau-Yosida $f$ -divergences Dávid Terjék 60 6 0 26 Feb 2021
Fast rates in structured prediction Vivien A. Cabannes Alessandro Rudi Francis R. Bach 423 19 0 01 Feb 2021
A contribution to Optimal Transport on incomparable spaces Titouan Vayer OT 73 20 0 09 Nov 2020
Gradient Estimation with Stochastic Softmax Tricks Max B. Paulus Dami Choi Daniel Tarlow Andreas Krause Chris J. Maddison BDL 101 88 0 15 Jun 2020
Fast Differentiable Sorting and Ranking Mathieu Blondel O. Teboul Quentin Berthet Josip Djolonga 212 235 0 20 Feb 2020
Learning with Differentiable Perturbed Optimizers Quentin Berthet Mathieu Blondel O. Teboul Marco Cuturi Jean-Philippe Vert Francis R. Bach 94 109 0 20 Feb 2020
Structured Prediction with Projection Oracles Mathieu Blondel 118 33 0 24 Oct 2019
Semantic Role Labeling with Iterative Structure Refinement Chunchuan Lyu Shay B. Cohen Ivan Titov OffRL 77 22 0 07 Sep 2019
The Limited Multi-Label Projection Layer Brandon Amos V. Koltun J. Zico Kolter 95 36 0 20 Jun 2019
Geometric Losses for Distributional Learning A. Mensch Mathieu Blondel Gabriel Peyré 143 16 0 15 May 2019
Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms Mathieu Blondel André F. T. Martins Vlad Niculae FedML 67 40 0 24 May 2018