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Francesco Orabona

51 papers · 2009–2026 · 12 venues · across top CS/AI venues

This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 21 separate collaboration groups - the largest holds only 47% of them. Pick the group below that matches the researcher you mean. How a shared name is split.

Achievements are not shown for a combined profile - each one describes a single researcher's record, which this is not.

Which Francesco Orabona?

5 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.

with Ashok Cutkosky, Kwang-Sung Jun, Barbara Caputo 24 papers · 2009–2025 · ICML, COLT, ALT Hide ▲
A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO ICML 2025 Square$χ$PO: Differentially Private and Robust $χ^2$-Preference Optimization in Offline Direct Alignment ICML 2025 Better-than-KL PAC-Bayes Bounds COLT 2024 Generalized Implicit Follow-The-Regularized-Leader ICML 2023 Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion ICML 2023 Tighter PAC-Bayes Bounds Through Coin-Betting COLT 2023 Better Parameter-Free Stochastic Optimization with ODE Updates for Coin-Betting AAAI 2022 Implicit Parameter-free Online Learning with Truncated Linear Models ALT 2022 On the Initialization for Convex-Concave Min-max Problems ALT 2022 On the Last Iterate Convergence of Momentum Methods ALT 2022 Robustness to Unbounded Smoothness of Generalized SignSGD NeurIPS 2022 A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance ICML 2021 Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration NeurIPS 2019 Momentum-Based Variance Reduction in Non-Convex SGD NeurIPS 2019 On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes AISTATS 2019 Parameter-Free Online Convex Optimization with Sub-Exponential Noise COLT 2019 Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization ICML 2019 Black-Box Reductions for Parameter-free Online Learning in Banach Spaces COLT 2018 Improved Strongly Adaptive Online Learning using Coin Betting AISTATS 2017 From N to N+1: Multiclass Transfer Incremental Learning CVPR 2013 Multiclass Latent Locally Linear Support Vector Machines ACML 2013 Stability and Hypothesis Transfer Learning ICML 2013 Multi Kernel Learning with Online-Batch Optimization JMLR 2012 Bounded Kernel-Based Online Learning JMLR 2009
16 papers whose co-authors appear nowhere else under this name
Cards Against Contamination: TCG-Bench for Difficulty-Scalable Multilingual LLM Reasoning EACL 2026 Self-Directed Node Classification on Graphs ALT 2025 An Equivalence Between Static and Dynamic Regret Minimization NeurIPS 2024 Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion ICLR 2024 Algorithmic Learning Theory 2023: Preface ALT 2023 Online Learning with Optimism and Delay ICML 2021 Efficient Online Bandit Multiclass Learning with Õ(√T) Regret ICML 2017 Training Deep Networks without Learning Rates Through Coin Betting NeurIPS 2017 Solving Ridge Regression using Sketched Preconditioned SVRG ICML 2016 On Measure Concentration of Random Maximum A-Posteriori Perturbations ICML 2014 Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning NeurIPS 2014 Unconstrained Online Linear Learning in Hilbert Spaces: Minimax Algorithms and Normal Approximations COLT 2014 Dimension-Free Exponentiated Gradient NeurIPS 2013 Regression-tree Tuning in a Streaming Setting NeurIPS 2013 Learning from Candidate Labeling Sets NeurIPS 2010 New Adaptive Algorithms for Online Classification NeurIPS 2010

Venues · all papers under this name

NeurIPS (14) ICML (12) COLT (8) ALT (5) AISTATS (3) JMLR (3) AAAI (1) ACML (1) AutoML (1) CVPR (1) EACL (1) ICLR (1)