Carlo Ciliberto
27 papers · 2014–2024 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (35) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Deep Specialist
(10)
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Dynamic Duo
(14)
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Keyword Champion
(2)
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Prolific Year Β· Productive
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Unstoppable Β· Bronze
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Keyword Collector
(120)
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(22)
Core Methods
(18)
Optimization & Theory
(13)
Artificial Intelligence
(9)
Learning Paradigms Β· Artificial Intelligence
(8)
Mathematics & Optimization
(6)
Learning Types Β· Machine Learning
(6)
Optimization
(5)
Deep Learning
(3)
Learning Paradigms Β· Machine Learning
(3)
Mathematics
(3)
Computer Vision
(2)
Reinforcement Learning
(2)
Learning Types Β· Deep Learning
(2)
Methods
(2)
Keywords
structured prediction
(7)
multi-task learning
(5)
transfer learning
(4)
optimal transport
(3)
reproducing kernel hilbert space
(3)
few-shot learning
(2)
biased regularization
(2)
conditional meta-learning
(2)
sinkhorn divergence
(2)
task distribution
(2)
manifold learning
(2)
representation learning
(2)
task adaptation
(2)
convex optimization
(2)
online learning
(2)
manifold regression
(2)
learning to learn
(2)
maximum mean discrepancy
(2)
kernel methods
(2)
variational inference
(1)
Papers
Operator World Models for Reinforcement Learning
NeurIPS 2024
Conditional Meta-Learning of Linear Representations
NeurIPS 2022
Distribution Regression with Sliced Wasserstein Kernels
ICML 2022
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces
NeurIPS 2022
Measuring dissimilarity with diffeomorphism invariance
ICML 2022
PSD Representations for Effective Probability Models
NeurIPS 2021
The Role of Global Labels in Few-Shot Classification and How to Infer Them
NeurIPS 2021
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings
JMLR 2020
Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning
NeurIPS 2020
Hyperbolic Manifold Regression
AISTATS 2020
Structured Prediction for Conditional Meta-Learning
NeurIPS 2020
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine Tuning
NeurIPS 2020
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization
ICML 2019
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction
ICML 2019
Localized Structured Prediction
NeurIPS 2019
Online-Within-Online Meta-Learning
NeurIPS 2019
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation
ICML 2019
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm
NeurIPS 2019
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance
NeurIPS 2018
Learning To Learn Around A Common Mean
NeurIPS 2018
Manifold Structured Prediction
NeurIPS 2018
Consistent Multitask Learning with Nonlinear Output Relations
NeurIPS 2017
Low Compute and Fully Parallel Computer Vision With HashMatch
ICCV 2017
A Consistent Regularization Approach for Structured Prediction
NeurIPS 2016
Convex Learning of Multiple Tasks and their Structure
ICML 2015
Learning Multiple Visual Tasks While Discovering Their Structure
CVPR 2015
Ask the Image: Supervised Pooling to Preserve Feature Locality
CVPR 2014