Orabona, Francesco

70 publications

ICML 2025 A Unified Theoretical Analysis of Private and Robust Offline Alignment: From RLHF to DPO Xingyu Zhou, Yulian Wu, Francesco Orabona

ICML 2025 ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning Arto Maranjyan, El Mehdi Saad, Peter Richtárik, Francesco Orabona

NeurIPS 2025 Dynamic Regret Reduces to Kernelized Static Regret Andrew Jacobsen, Alessandro Rudi, Francesco Orabona, Nicolò Cesa-Bianchi

COLT 2025 New Lower Bounds for Non-Convex Stochastic Optimization Through Divergence Decomposition El Mehdi Saad, Wei-Cheng Lee, Francesco Orabona

NeurIPS 2025 New Perspectives on the Polyak Stepsize: Surrogate Functions and Negative Results Francesco Orabona, Ryan D'Orazio

NeurIPS 2025 Optimal Regret of Bandits Under Differential Privacy Achraf Azize, Yulian Wu, Junya Honda, Francesco Orabona, Shinji Ito, Debabrota Basu

NeurIPS 2025 Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track Rylan Schaeffer, Joshua Kazdan, Yegor Denisov-Blanch, Brando Miranda, Matthias Gerstgrasser, Susan Zhang, Andreas Haupt, Isha Gupta, Elyas Obbad, Jesse Dodge, Jessica Zosa Forde, Francesco Orabona, Sanmi Koyejo, David L. Donoho

NeurIPS 2025 STAR-Bets: Sequential TArget-Recalculating Bets for Tighter Confidence Intervals Vaclav Voracek, Francesco Orabona

ALT 2025 Self-Directed Node Classification on Graphs Georgy Sokolov, Maximilian Thiessen, Margarita Akhmejanova, Fabio Vitale, Francesco Orabona

ICML 2025 Square$χ$PO: Differentially Private and Robust $χ^2$-Preference Optimization in Offline Direct Alignment Xingyu Zhou, Yulian Wu, Wenqian Weng, Francesco Orabona

NeurIPS 2024 An Equivalence Between Static and Dynamic Regret Minimization Andrew Jacobsen, Francesco Orabona

COLT 2024 Better-than-KL PAC-Bayes Bounds Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona

ICLR 2024 Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion Alexandru Meterez, Amir Joudaki, Francesco Orabona, Alexander Immer, Gunnar Ratsch, Hadi Daneshmand

ALT 2023 Algorithmic Learning Theory 2023: Preface Shipra Agrawal, Francesco Orabona

ICML 2023 Generalized Implicit Follow-the-Regularized-Leader Keyi Chen, Francesco Orabona

ICML 2023 Optimal Stochastic Non-Smooth Non-Convex Optimization Through Online-to-Non-Convex Conversion Ashok Cutkosky, Harsh Mehta, Francesco Orabona

COLT 2023 Tighter PAC-Bayes Bounds Through Coin-Betting Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona

AAAI 2022 Better Parameter-Free Stochastic Optimization with ODE Updates for Coin-Betting Keyi Chen, John Langford, Francesco Orabona

ALT 2022 Implicit Parameter-Free Online Learning with Truncated Linear Models Keyi Chen, Ashok Cutkosky, Francesco Orabona

ALT 2022 On the Initialization for Convex-Concave Min-Max Problems Mingrui Liu, Francesco Orabona

ALT 2022 On the Last Iterate Convergence of Momentum Methods Xiaoyu Li, Mingrui Liu, Francesco Orabona

NeurIPS 2022 Robustness to Unbounded Smoothness of Generalized SignSGD Michael Crawshaw, Mingrui Liu, Francesco Orabona, Wei Zhang, Zhenxun Zhuang

TMLR 2022 Understanding AdamW Through Proximal Methods and Scale-Freeness Zhenxun Zhuang, Mingrui Liu, Ashok Cutkosky, Francesco Orabona

ICML 2021 A Second Look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona

NeurIPS 2021 Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers Jeffrey Negrea, Blair Bilodeau, Nicolò Campolongo, Francesco Orabona, Dan Roy

ICML 2021 Online Learning with Optimism and Delay Genevieve E Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey

NeurIPS 2020 Temporal Variability in Implicit Online Learning Nicolò Campolongo, Francesco Orabona

NeurIPS 2019 Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration Kwang-Sung Jun, Ashok Cutkosky, Francesco Orabona

NeurIPS 2019 Momentum-Based Variance Reduction in Non-Convex SGD Ashok Cutkosky, Francesco Orabona

AISTATS 2019 On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes Xiaoyu Li, Francesco Orabona

COLT 2019 Parameter-Free Online Convex Optimization with Sub-Exponential Noise Kwang-Sung Jun, Francesco Orabona

ICML 2019 Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization Zhenxun Zhuang, Ashok Cutkosky, Francesco Orabona

COLT 2018 Black-Box Reductions for Parameter-Free Online Learning in Banach Spaces Ashok Cutkosky, Francesco Orabona

ICML 2017 Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret Alina Beygelzimer, Francesco Orabona, Chicheng Zhang

MLJ 2017 Fast Rates by Transferring from Auxiliary Hypotheses Ilja Kuzborskij, Francesco Orabona

AISTATS 2017 Improved Strongly Adaptive Online Learning Using Coin Betting Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett

NeurIPS 2017 Training Deep Networks Without Learning Rates Through Coin Betting Francesco Orabona, Tatiana Tommasi

NeurIPS 2016 Coin Betting and Parameter-Free Online Learning Francesco Orabona, David Pal

COLT 2016 Open Problem: Parameter-Free and Scale-Free Online Algorithms Francesco Orabona, Dávid Pál

AutoML 2016 Parameter-Free Convex Learning Through Coin Betting Francesco Orabona, Dávid Pál

ICML 2016 Solving Ridge Regression Using Sketched Preconditioned SVRG Alon Gonen, Francesco Orabona, Shai Shalev-Shwartz

MLJ 2015 A Generalized Online Mirror Descent with Applications to Classification and Regression Francesco Orabona, Koby Crammer, Nicolò Cesa-Bianchi

ALT 2015 Scale-Free Algorithms for Online Linear Optimization Francesco Orabona, Dávid Pál

ICML 2014 On Measure Concentration of Random Maximum A-Posteriori Perturbations Francesco Orabona, Tamir Hazan, Anand Sarwate, Tommi Jaakkola

JMLR 2014 On Multilabel Classification and Ranking with Bandit Feedback Claudio Gentile, Francesco Orabona

NeurIPS 2014 Simultaneous Model Selection and Optimization Through Parameter-Free Stochastic Learning Francesco Orabona

COLT 2014 Unconstrained Online Linear Learning in Hilbert Spaces: Minimax Algorithms and Normal Approximations H. Brendan McMahan, Francesco Orabona

NeurIPS 2013 Dimension-Free Exponentiated Gradient Francesco Orabona

CVPR 2013 From N to N+1: Multiclass Transfer Incremental Learning Ilja Kuzborskij, Francesco Orabona, Barbara Caputo

ACML 2013 Multiclass Latent Locally Linear Support Vector Machines Marco Fornoni, Barbara Caputo, Francesco Orabona

NeurIPS 2013 Regression-Tree Tuning in a Streaming Setting Samory Kpotufe, Francesco Orabona

ICML 2013 Stability and Hypothesis Transfer Learning Ilja Kuzborskij, Francesco Orabona

AISTATS 2012 Beyond Logarithmic Bounds in Online Learning Francesco Orabona, Nicolo Cesa-Bianchi, Claudio Gentile

JMLR 2012 Multi Kernel Learning with Online-Batch Optimization Francesco Orabona, Luo Jie, Barbara Caputo

NeurIPS 2012 On Multilabel Classification and Ranking with Partial Feedback Claudio Gentile, Francesco Orabona

ICML 2011 Better Algorithms for Selective Sampling Francesco Orabona, Nicolò Cesa-Bianchi

ICML 2011 Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning Francesco Orabona, Jie Luo

NeurIPS 2010 Learning from Candidate Labeling Sets Jie Luo, Francesco Orabona

NeurIPS 2010 New Adaptive Algorithms for Online Classification Francesco Orabona, Koby Crammer

CVPRW 2010 OM-2: An Online Multi-Class Multi-Kernel Learning Algorithm Luo Jie Francesco Orabona, Marco Fornoni, Barbara Caputo, Nicolò Cesa-Bianchi

CVPR 2010 Online-Batch Strongly Convex Multi Kernel Learning Francesco Orabona, Jie Luo, Barbara Caputo

CVPR 2010 Safety in Numbers: Learning Categories from Few Examples with Multi Model Knowledge Transfer Tatiana Tommasi, Francesco Orabona, Barbara Caputo

JMLR 2009 Bounded Kernel-Based Online Learning Francesco Orabona, Joseph Keshet, Barbara Caputo

ICML 2009 Robust Bounds for Classification via Selective Sampling Nicolò Cesa-Bianchi, Claudio Gentile, Francesco Orabona

ECCV 2008 Calibration from Statistical Properties of the Visual World Etienne Grossmann, José António Gaspar, Francesco Orabona

ICML 2008 The Projectron: A Bounded Kernel-Based Perceptron Francesco Orabona, Joseph Keshet, Barbara Caputo

ICCV 2007 Discrete Camera Calibration from the Information Distance Between Pixel Streams Etienne Grossmann, Francesco Orabona, José António Gaspar

CVPRW 2006 Learning Association Fields from Natural Images Francesco Orabona, Giorgio Metta, Giulio Sandini

CVPR 2005 Object-Based Visual Attention: A Model for a Behaving Robot Francesco Orabona, Giorgio Metta, Giulio Sandini

CVPRW 2005 Object-Based Visual Attention: A Model for a Behaving Robot Francesco Orabona, Giorgio Metta, Giulio Sandini