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On Structured Prediction Theory with Calibrated Convex Surrogate Losses
7 March 2017
A. Osokin
Francis R. Bach
Damien Scieur
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Papers citing
"On Structured Prediction Theory with Calibrated Convex Surrogate Losses"
41 / 41 papers shown
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Self-Supervised Penalty-Based Learning for Robust Constrained Optimization
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Proper losses regret at least 1/2-order
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A Universal Growth Rate for Learning with Smooth Surrogate Losses
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09 May 2024
H
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H
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Online Structured Prediction with Fenchel--Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss
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Cross-Entropy Loss Functions: Theoretical Analysis and Applications
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M. Mohri
Yutao Zhong
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14 Apr 2023
Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
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Luc Brogat-Motte
Pierre Laforgue
Florence dÁlché-Buc
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401
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20 Feb 2023
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates
Journal of machine learning research (JMLR), 2022
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282
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29 Jun 2022
Learning Energy Networks with Generalized Fenchel-Young Losses
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Felipe Llinares-López
Robert Dadashi
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293
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0
19 May 2022
The Structured Abstain Problem and the Lovász Hinge
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309
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16 Mar 2022
Surrogate Regret Bounds for Polyhedral Losses
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Bo Waggoner
144
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Risk Bounds and Calibration for a Smart Predict-then-Optimize Method
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Paul Grigas
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Contextual Inverse Optimization: Offline and Online Learning
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Omar Besbes
Yuri R. Fonseca
Ilan Lobel
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Risk Guarantees for End-to-End Prediction and Optimization Processes
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Nam Ho-Nguyen
Fatma Kılınç Karzan
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30 Dec 2020
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings
Théophile Cantelobre
Benjamin Guedj
Maria Perez-Ortiz
John Shawe-Taylor
430
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0
07 Dec 2020
Learning Output Embeddings in Structured Prediction
Luc Brogat-Motte
Alessandro Rudi
Céline Brouard
Juho Rousu
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29 Jul 2020
Consistent Structured Prediction with Max-Min Margin Markov Networks
Alex Nowak-Vila
Francis R. Bach
Alessandro Rudi
319
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Calibrated Surrogate Losses for Adversarially Robust Classification
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Han Bao
Clayton Scott
Masashi Sugiyama
286
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28 May 2020
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings
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C. Ciliberto
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Alessandro Rudi
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13 Feb 2020
Structured Prediction with Projection Oracles
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Consistent Classification with Generalized Metrics
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196
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An Embedding Framework for Consistent Polyhedral Surrogates
Neural Information Processing Systems (NeurIPS), 2019
Jessie Finocchiaro
Rafael Frongillo
Bo Waggoner
314
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17 Jul 2019
Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Han Bao
Masashi Sugiyama
215
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29 May 2019
Strategic Prediction with Latent Aggregative Games
Vikas Garg
Tommi Jaakkola
173
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29 May 2019
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction
International Conference on Machine Learning (ICML), 2019
Giulia Luise
Dimitris Stamos
Massimiliano Pontil
C. Ciliberto
198
12
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02 Mar 2019
A General Theory for Structured Prediction with Smooth Convex Surrogates
Alex Nowak-Vila
Francis R. Bach
Alessandro Rudi
362
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05 Feb 2019
Distributionally Robust Graphical Models
Neural Information Processing Systems (NeurIPS), 2018
Rizal Fathony
Ashkan Rezaei
Takaaki Hori
Xinhua Zhang
T. Ogata
TPM
163
20
0
07 Nov 2018
Sharp Analysis of Learning with Discrete Losses
Alex Nowak-Vila
Francis R. Bach
Alessandro Rudi
257
23
0
16 Oct 2018
Learning with SGD and Random Features
Neural Information Processing Systems (NeurIPS), 2018
Luigi Carratino
Alessandro Rudi
Lorenzo Rosasco
301
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17 Jul 2018
A Structured Prediction Approach for Label Ranking
Neural Information Processing Systems (NeurIPS), 2018
Anna Korba
Alexandre Garcia
Florence dÁlché-Buc
214
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06 Jul 2018
Localized Structured Prediction
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Francis R. Bach
Alessandro Rudi
224
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06 Jun 2018
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance
Giulia Luise
Alessandro Rudi
Massimiliano Pontil
C. Ciliberto
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296
140
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30 May 2018
Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes
Loucas Pillaud-Vivien
Alessandro Rudi
Francis R. Bach
419
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25 May 2018
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
Alexandre Garcia
S. Essid
Chloé Clavel
Florence dÁlché-Buc
210
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22 Mar 2018
Exponential convergence of testing error for stochastic gradient methods
Loucas Pillaud-Vivien
Alessandro Rudi
Francis R. Bach
312
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13 Dec 2017
Smart "Predict, then Optimize"
Management Sciences (MS), 2017
Adam N. Elmachtoub
Paul Grigas
679
801
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22 Oct 2017
Parametric Adversarial Divergences are Good Losses for Generative Modeling
Gabriel Huang
Hugo Berard
Ahmed Touati
Gauthier Gidel
Pascal Vincent
Damien Scieur
GAN
374
1
0
08 Aug 2017
On the Consistency of Ordinal Regression Methods
Journal of machine learning research (JMLR), 2014
Fabian Pedregosa
Francis R. Bach
Alexandre Gramfort
MoMe
584
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11 Aug 2014
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