Francesco Orabona

Orcid: 0000-0001-8523-6845

Affiliations:
  • King Abdullah University of Science and Technology, Saudi Arabia


According to our database1, Francesco Orabona authored at least 103 papers between 2005 and 2024.

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Bibliography

2024
Tight Concentrations and Confidence Sequences From the Regret of Universal Portfolio.
IEEE Trans. Inf. Theory, January, 2024

Self-Directed Learning of Convex Labelings on Graphs.
CoRR, 2024

An Equivalence Between Static and Dynamic Regret Minimization.
CoRR, 2024

Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Better-than-KL PAC-Bayes Bounds.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023
Normalized Gradients for All.
CoRR, 2023

Implicit Interpretation of Importance Weight Aware Updates.
CoRR, 2023

Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion.
Proceedings of the International Conference on Machine Learning, 2023

Generalized Implicit Follow-The-Regularized-Leader.
Proceedings of the International Conference on Machine Learning, 2023

Tighter PAC-Bayes Bounds Through Coin-Betting.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Understanding AdamW through Proximal Methods and Scale-Freeness.
Trans. Mach. Learn. Res., 2022

Robustness to Unbounded Smoothness of Generalized SignSGD.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Initialization for Convex-Concave Min-max Problems.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

On the Last Iterate Convergence of Momentum Methods.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Implicit Parameter-free Online Learning with Truncated Linear Models.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Better Parameter-Free Stochastic Optimization with ODE Updates for Coin-Betting.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
A Parameter-free Algorithm for Convex-concave Min-max Problems.
CoRR, 2021

A closer look at temporal variability in dynamic online learning.
CoRR, 2021

Parameter-free Stochastic Optimization of Variationally Coherent Functions.
CoRR, 2021

Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance.
Proceedings of the 38th International Conference on Machine Learning, 2021

Online Learning with Optimism and Delay.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Adam<sup>+</sup>: A Stochastic Method with Adaptive Variance Reduction.
CoRR, 2020

A High Probability Analysis of Adaptive SGD with Momentum.
CoRR, 2020

Exponential Step Sizes for Non-Convex Optimization.
CoRR, 2020

Temporal Variability in Implicit Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
High Dimensional Inference With Random Maximum A-Posteriori Perturbations.
IEEE Trans. Inf. Theory, 2019

A Modern Introduction to Online Learning.
CoRR, 2019

Parameter-Free Locally Differentially Private Stochastic Subgradient Descent.
CoRR, 2019

Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Momentum-Based Variance Reduction in Non-Convex SGD.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization.
Proceedings of the 36th International Conference on Machine Learning, 2019

Parameter-Free Online Convex Optimization with Sub-Exponential Noise.
Proceedings of the Conference on Learning Theory, 2019

On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Scale-free online learning.
Theor. Comput. Sci., 2018

Black-Box Reductions for Parameter-free Online Learning in Banach Spaces.
Proceedings of the Conference On Learning Theory, 2018

2017
Fast rates by transferring from auxiliary hypotheses.
Mach. Learn., 2017

Scalable greedy algorithms for transfer learning.
Comput. Vis. Image Underst., 2017

Online Learning for Changing Environments using Coin Betting.
CoRR, 2017

Backprop without Learning Rates Through Coin Betting.
CoRR, 2017

Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret.
CoRR, 2017

Training Deep Networks without Learning Rates Through Coin Betting.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Efficient Online Bandit Multiclass Learning with Õ(√T) Regret.
Proceedings of the 34th International Conference on Machine Learning, 2017

Improved Strongly Adaptive Online Learning using Coin Betting.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
From Coin Betting to Parameter-Free Online Learning.
CoRR, 2016

Coin Betting and Parameter-Free Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Parameter-Free Convex Learning through Coin Betting.
Proceedings of the 2016 Workshop on Automatic Machine Learning, 2016

Solving Ridge Regression using Sketched Preconditioned SVRG.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Open Problem: Parameter-Free and Scale-Free Online Algorithms.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
A generalized online mirror descent with applications to classification and regression.
Mach. Learn., 2015

Optimal Non-Asymptotic Lower Bound on the Minimax Regret of Learning with Expert Advice.
CoRR, 2015

A Simple Expression for Mill's Ratio of the Student's t-Distribution.
CoRR, 2015

Transfer Learning Through Greedy Subset Selection.
Proceedings of the Image Analysis and Processing - ICIAP 2015, 2015

The ABACOC Algorithm: A Novel Approach for Nonparametric Classification of Data Streams.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Scale-Free Algorithms for Online Linear Optimization.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

2014
Learning Categories From Few Examples With Multi Model Knowledge Transfer.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

On multilabel classification and ranking with bandit feedback.
J. Mach. Learn. Res., 2014

Learning by Transferring from Auxiliary Hypotheses.
CoRR, 2014

Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On Measure Concentration of Random Maximum A-Posteriori Perturbations.
Proceedings of the 31th International Conference on Machine Learning, 2014

Unconstrained Online Linear Learning in Hilbert Spaces: Minimax Algorithms and Normal Approximations.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Improving Control of Dexterous Hand Prostheses Using Adaptive Learning.
IEEE Trans. Robotics, 2013

Dimension-Free Exponentiated Gradient.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Regression-tree Tuning in a Streaming Setting.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Stability and Hypothesis Transfer Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

From N to N+1: Multiclass Transfer Incremental Learning.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

Multiclass Latent Locally Linear Support Vector Machines.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
Multi Kernel Learning with Online-Batch Optimization.
J. Mach. Learn. Res., 2012

Beyond Logarithmic Bounds in Online Learning.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

PRISMA: PRoximal Iterative SMoothing Algorithm
CoRR, 2012

On Multilabel Classification and Ranking with Partial Feedback.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Leveraging over prior knowledge for online learning of visual categories.
Proceedings of the British Machine Vision Conference, 2012

2011
Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning.
Proceedings of the 28th International Conference on Machine Learning, 2011

Better Algorithms for Selective Sampling.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
On-line independent support vector machines.
Pattern Recognit., 2010

Discrete camera calibration from pixel streams.
Comput. Vis. Image Underst., 2010

New Adaptive Algorithms for Online Classification.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Learning from Candidate Labeling Sets.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Safety in numbers: Learning categories from few examples with multi model knowledge transfer.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Online-batch strongly convex Multi Kernel Learning.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

OM-2: An online multi-class Multi-Kernel Learning algorithm Luo Jie.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2010

Idiap on Medical Image Classification.
Proceedings of the ImageCLEF, Experimental Evaluation in Visual Information Retrieval, 2010

2009
Bounded Kernel-Based Online Learning.
J. Mach. Learn. Res., 2009

You live, you learn, you forget: Continuous learning of visual places with a forgetting mechanism.
Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

Model adaptation with least-squares SVM for adaptive hand prosthetics.
Proceedings of the 2009 IEEE International Conference on Robotics and Automation, 2009

Robust bounds for classification via selective sampling.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

An Online Framework for Learning Novel Concepts over Multiple Cues.
Proceedings of the Computer Vision, 2009

2008
Discriminative cue integration for medical image annotation.
Pattern Recognit. Lett., 2008

The projectron: a bounded kernel-based Perceptron.
Proceedings of the Machine Learning, 2008

Calibration from Statistical Properties of the Visual World.
Proceedings of the Computer Vision, 2008

CLEF2008 Image Annotation Task: an SVM Confidence-Based Approach.
Proceedings of the Working Notes for CLEF 2008 Workshop co-located with the 12th European Conference on Digital Libraries (ECDL 2008) , 2008

An SVM Confidence-Based Approach to Medical Image Annotation.
Proceedings of the Evaluating Systems for Multilingual and Multimodal Information Access, 2008

2007
Internal models of reaching and grasping.
Adv. Robotics, 2007

A Proto-object Based Visual Attention Model.
Proceedings of the Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint, 2007

Discrete camera calibration from the information distance between pixel streams.
Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

CLEF2007: Image Annotation Task: an SVM-based Cue Integration Approach.
Proceedings of the Working Notes for CLEF 2007 Workshop co-located with the 11th European Conference on Digital Libraries (ECDL 2007), 2007

Cue Integration for Medical Image Annotation.
Proceedings of the Advances in Multilingual and Multimodal Information Retrieval, 2007

Indoor Place Recognition using Online Independent Support Vector Machines.
Proceedings of the British Machine Vision Conference 2007, 2007

2006
Simulation and Assessment of Bioinspired Visual Processing System for Epi-retinal Prostheses.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

Learning Association Fields from Natural Images.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006

2005
From sensorimotor development to object perception.
Proceedings of the 5th IEEE-RAS International Conference on Humanoid Robots, 2005

Object-based Visual Attention: a Model for a Behaving Robot.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005

Exploring the world through grasping: a developmental approach.
Proceedings of the CIRA 2005, 2005


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