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ORCIDFrancesco Orabona
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- affiliation: King Abdullah University of Science and Technology, Saudi Arabia
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2020 – today
- 2024
[j16]Francesco Orabona
, Kwang-Sung Jun:
Tight Concentrations and Confidence Sequences From the Regret of Universal Portfolio. IEEE Trans. Inf. Theory 70(1): 436-455 (2024)- [c66]Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona:
Better-than-KL PAC-Bayes Bounds. COLT 2024: 3325-3352 - [c65]Alexandru Meterez, Amir Joudaki, Francesco Orabona, Alexander Immer, Gunnar Rätsch, Hadi Daneshmand:
Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion. ICLR 2024 - [i52]Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona:
Better-than-KL PAC-Bayes Bounds. CoRR abs/2402.09201 (2024) - [i51]Andrew Jacobsen, Francesco Orabona:
An Equivalence Between Static and Dynamic Regret Minimization. CoRR abs/2406.01577 (2024) - [i50]Georgy Sokolov, Maximilian Thiessen, Margarita Akhmejanova, Fabio Vitale, Francesco Orabona:
Self-Directed Learning of Convex Labelings on Graphs. CoRR abs/2409.01428 (2024) - 2023
- [c64]Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona:
Tighter PAC-Bayes Bounds Through Coin-Betting. COLT 2023: 2240-2264 - [c63]Keyi Chen, Francesco Orabona:
Generalized Implicit Follow-The-Regularized-Leader. ICML 2023: 4826-4838 - [c62]Ashok Cutkosky, Harsh Mehta, Francesco Orabona:
Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion. ICML 2023: 6643-6670 - [e1]Shipra Agrawal, Francesco Orabona:
International Conference on Algorithmic Learning Theory, February 20-23, 2023, Singapore. Proceedings of Machine Learning Research 201, PMLR 2023 [contents] - [i49]Ashok Cutkosky, Harsh Mehta, Francesco Orabona:
Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion. CoRR abs/2302.03775 (2023) - [i48]Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona:
Tighter PAC-Bayes Bounds Through Coin-Betting. CoRR abs/2302.05829 (2023) - [i47]Keyi Chen, Francesco Orabona:
Generalized Implicit Follow-The-Regularized-Leader. CoRR abs/2306.00201 (2023) - [i46]Keyi Chen, Francesco Orabona:
Implicit Interpretation of Importance Weight Aware Updates. CoRR abs/2307.11955 (2023) - [i45]Francesco Orabona:
Normalized Gradients for All. CoRR abs/2308.05621 (2023) - [i44]Alexandru Meterez, Amir Joudaki, Francesco Orabona, Alexander Immer, Gunnar Rätsch, Hadi Daneshmand:
Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion. CoRR abs/2310.02012 (2023) - 2022
- [j15]Zhenxun Zhuang, Mingrui Liu, Ashok Cutkosky, Francesco Orabona:
Understanding AdamW through Proximal Methods and Scale-Freeness. Trans. Mach. Learn. Res. 2022 (2022) - [c61]Keyi Chen, John Langford, Francesco Orabona:
Better Parameter-Free Stochastic Optimization with ODE Updates for Coin-Betting. AAAI 2022: 6239-6247 - [c60]Keyi Chen, Ashok Cutkosky, Francesco Orabona:
Implicit Parameter-free Online Learning with Truncated Linear Models. ALT 2022: 148-175 - [c59]Xiaoyu Li, Mingrui Liu, Francesco Orabona:
On the Last Iterate Convergence of Momentum Methods. ALT 2022: 699-717 - [c58]Mingrui Liu, Francesco Orabona:
On the Initialization for Convex-Concave Min-max Problems. ALT 2022: 743-767 - [c57]Michael Crawshaw, Mingrui Liu, Francesco Orabona, Wei Zhang, Zhenxun Zhuang:
Robustness to Unbounded Smoothness of Generalized SignSGD. NeurIPS 2022 - [i43]Zhenxun Zhuang, Mingrui Liu, Ashok Cutkosky, Francesco Orabona:
Understanding AdamW through Proximal Methods and Scale-Freeness. CoRR abs/2202.00089 (2022) - [i42]Keyi Chen, Ashok Cutkosky, Francesco Orabona:
Implicit Parameter-free Online Learning with Truncated Linear Models. CoRR abs/2203.10327 (2022) - [i41]Michael Crawshaw, Mingrui Liu, Francesco Orabona, Wei Zhang, Zhenxun Zhuang:
Robustness to Unbounded Smoothness of Generalized SignSGD. CoRR abs/2208.11195 (2022) - 2021
- [c56]Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey:
Online Learning with Optimism and Delay. ICML 2021: 3363-3373 - [c55]Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona:
A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance. ICML 2021: 6553-6564 - [c54]Jeffrey Negrea, Blair L. Bilodeau, Nicolò Campolongo, Francesco Orabona, Daniel M. Roy:
Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers. NeurIPS 2021: 26237-26249 - [i40]Francesco Orabona, Dávid Pál:
Parameter-free Stochastic Optimization of Variationally Coherent Functions. CoRR abs/2102.00236 (2021) - [i39]Xiaoyu Li, Mingrui Liu, Francesco Orabona:
On the Last Iterate Convergence of Momentum Methods. CoRR abs/2102.07002 (2021) - [i38]Nicolò Campolongo, Francesco Orabona:
A closer look at temporal variability in dynamic online learning. CoRR abs/2102.07666 (2021) - [i37]Mingrui Liu, Francesco Orabona:
A Parameter-free Algorithm for Convex-concave Min-max Problems. CoRR abs/2103.00284 (2021) - [i36]Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey:
Online Learning with Optimism and Delay. CoRR abs/2106.06885 (2021) - [i35]Francesco Orabona, Kwang-Sung Jun:
Tight Concentrations and Confidence Sequences from the Regret of Universal Portfolio. CoRR abs/2110.14099 (2021) - [i34]Jeffrey Negrea, Blair L. Bilodeau, Nicolò Campolongo, Francesco Orabona, Daniel M. Roy:
Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers. CoRR abs/2110.14804 (2021) - 2020
- [c53]Nicolò Campolongo, Francesco Orabona:
Temporal Variability in Implicit Online Learning. NeurIPS 2020 - [i33]Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona:
Exponential Step Sizes for Non-Convex Optimization. CoRR abs/2002.05273 (2020) - [i32]Nicolò Campolongo, Francesco Orabona:
Temporal Variability in Implicit Online Learning. CoRR abs/2006.07503 (2020) - [i31]Keyi Chen, John Langford, Francesco Orabona:
Better Parameter-free Stochastic Optimization with ODE Updates for Coin-Betting. CoRR abs/2006.07507 (2020) - [i30]Xiaoyu Li, Francesco Orabona:
A High Probability Analysis of Adaptive SGD with Momentum. CoRR abs/2007.14294 (2020) - [i29]Mingrui Liu, Wei Zhang, Francesco Orabona, Tianbao Yang:
Adam+: A Stochastic Method with Adaptive Variance Reduction. CoRR abs/2011.11985 (2020)
2010 – 2019
- 2019
- [j14]Tamir Hazan, Francesco Orabona, Anand D. Sarwate, Subhransu Maji, Tommi S. Jaakkola:
High Dimensional Inference With Random Maximum A-Posteriori Perturbations. IEEE Trans. Inf. Theory 65(10): 6539-6560 (2019) - [c52]Xiaoyu Li, Francesco Orabona:
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes. AISTATS 2019: 983-992 - [c51]Kwang-Sung Jun, Francesco Orabona:
Parameter-Free Online Convex Optimization with Sub-Exponential Noise. COLT 2019: 1802-1823 - [c50]Zhenxun Zhuang, Ashok Cutkosky, Francesco Orabona:
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization. ICML 2019: 7664-7672 - [c49]Ashok Cutkosky, Francesco Orabona:
Momentum-Based Variance Reduction in Non-Convex SGD. NeurIPS 2019: 15210-15219 - [c48]Kwang-Sung Jun, Ashok Cutkosky, Francesco Orabona:
Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration. NeurIPS 2019: 15332-15341 - [i28]Zhenxun Zhuang, Ashok Cutkosky, Francesco Orabona:
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization. CoRR abs/1901.09068 (2019) - [i27]Kwang-Sung Jun, Francesco Orabona:
Parameter-free Online Convex Optimization with Sub-Exponential Noise. CoRR abs/1902.01500 (2019) - [i26]Ashok Cutkosky, Francesco Orabona:
Momentum-Based Variance Reduction in Non-Convex SGD. CoRR abs/1905.10018 (2019) - [i25]Kwang-Sung Jun, Ashok Cutkosky, Francesco Orabona:
Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration. CoRR abs/1905.10680 (2019) - [i24]Kwang-Sung Jun, Francesco Orabona:
Parameter-Free Locally Differentially Private Stochastic Subgradient Descent. CoRR abs/1911.09564 (2019) - [i23]Francesco Orabona:
A Modern Introduction to Online Learning. CoRR abs/1912.13213 (2019) - 2018
- [j13]Francesco Orabona, Dávid Pál:
Scale-free online learning. Theor. Comput. Sci. 716: 50-69 (2018) - [c47]Ashok Cutkosky, Francesco Orabona:
Black-Box Reductions for Parameter-free Online Learning in Banach Spaces. COLT 2018: 1493-1529 - [i22]Ashok Cutkosky, Francesco Orabona:
Black-Box Reductions for Parameter-free Online Learning in Banach Spaces. CoRR abs/1802.06293 (2018) - [i21]Xiaoyu Li, Francesco Orabona:
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes. CoRR abs/1805.08114 (2018) - 2017
- [j12]Ilja Kuzborskij, Francesco Orabona, Barbara Caputo:
Scalable greedy algorithms for transfer learning. Comput. Vis. Image Underst. 156: 174-185 (2017) - [j11]Ilja Kuzborskij, Francesco Orabona:
Fast rates by transferring from auxiliary hypotheses. Mach. Learn. 106(2): 171-195 (2017) - [c46]Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett:
Improved Strongly Adaptive Online Learning using Coin Betting. AISTATS 2017: 943-951 - [c45]Alina Beygelzimer, Francesco Orabona, Chicheng Zhang:
Efficient Online Bandit Multiclass Learning with Õ(√T) Regret. ICML 2017: 488-497 - [c44]Francesco Orabona, Tatiana Tommasi:
Training Deep Networks without Learning Rates Through Coin Betting. NIPS 2017: 2160-2170 - [i20]Alina Beygelzimer, Francesco Orabona, Chicheng Zhang:
Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret. CoRR abs/1702.07958 (2017) - [i19]Francesco Orabona, Tatiana Tommasi:
Backprop without Learning Rates Through Coin Betting. CoRR abs/1705.07795 (2017) - [i18]Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett:
Online Learning for Changing Environments using Coin Betting. CoRR abs/1711.02545 (2017) - 2016
- [c43]Francesco Orabona, Dávid Pál:
Open Problem: Parameter-Free and Scale-Free Online Algorithms. COLT 2016: 1659-1664 - [c42]Francesco Orabona, Dávid Pál:
Parameter-Free Convex Learning through Coin Betting. AutoML@ICML 2016: 75-82 - [c41]Alon Gonen, Francesco Orabona, Shai Shalev-Shwartz:
Solving Ridge Regression using Sketched Preconditioned SVRG. ICML 2016: 1397-1405 - [c40]Francesco Orabona, Dávid Pál:
Coin Betting and Parameter-Free Online Learning. NIPS 2016: 577-585 - [i17]Francesco Orabona, Dávid Pál:
Scale-Free Online Learning. CoRR abs/1601.01974 (2016) - [i16]Alon Gonen, Francesco Orabona, Shai Shalev-Shwartz:
Solving Ridge Regression using Sketched Preconditioned SVRG. CoRR abs/1602.02350 (2016) - [i15]Tamir Hazan, Francesco Orabona, Anand D. Sarwate, Subhransu Maji, Tommi S. Jaakkola:
High Dimensional Inference with Random Maximum A-Posteriori Perturbations. CoRR abs/1602.03571 (2016) - [i14]Francesco Orabona, Dávid Pál:
From Coin Betting to Parameter-Free Online Learning. CoRR abs/1602.04128 (2016) - [i13]Kwang-Sung Jun, Francesco Orabona, Rebecca Willett, Stephen J. Wright:
Improved Strongly Adaptive Online Learning using Coin Betting. CoRR abs/1610.04578 (2016) - 2015
- [j10]Francesco Orabona, Koby Crammer, Nicolò Cesa-Bianchi:
A generalized online mirror descent with applications to classification and regression. Mach. Learn. 99(3): 411-435 (2015) - [c39]Francesco Orabona, Dávid Pál:
Scale-Free Algorithms for Online Linear Optimization. ALT 2015: 287-301 - [c38]Rocco De Rosa, Francesco Orabona, Nicolò Cesa-Bianchi:
The ABACOC Algorithm: A Novel Approach for Nonparametric Classification of Data Streams. ICDM 2015: 733-738 - [c37]Ilja Kuzborskij, Francesco Orabona, Barbara Caputo:
Transfer Learning Through Greedy Subset Selection. ICIAP (1) 2015: 3-14 - [i12]Francesco Orabona:
A Simple Expression for Mill's Ratio of the Student's t-Distribution. CoRR abs/1502.01632 (2015) - [i11]Francesco Orabona, Dávid Pál:
Scale-Free Algorithms for Online Linear Optimization. CoRR abs/1502.05744 (2015) - [i10]Rocco De Rosa, Francesco Orabona, Nicolò Cesa-Bianchi:
The ABACOC Algorithm: a Novel Approach for Nonparametric Classification of Data Streams. CoRR abs/1508.04912 (2015) - [i9]Francesco Orabona, Dávid Pál:
Optimal Non-Asymptotic Lower Bound on the Minimax Regret of Learning with Expert Advice. CoRR abs/1511.02176 (2015) - 2014
- [j9]Claudio Gentile, Francesco Orabona:
On multilabel classification and ranking with bandit feedback. J. Mach. Learn. Res. 15(1): 2451-2487 (2014) - [j8]Tatiana Tommasi, Francesco Orabona, Barbara Caputo:
Learning Categories From Few Examples With Multi Model Knowledge Transfer. IEEE Trans. Pattern Anal. Mach. Intell. 36(5): 928-941 (2014) - [c36]H. Brendan McMahan, Francesco Orabona:
Unconstrained Online Linear Learning in Hilbert Spaces: Minimax Algorithms and Normal Approximations. COLT 2014: 1020-1039 - [c35]Francesco Orabona, Tamir Hazan, Anand D. Sarwate, Tommi S. Jaakkola:
On Measure Concentration of Random Maximum A-Posteriori Perturbations. ICML 2014: 432-440 - [c34]Francesco Orabona:
Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning. NIPS 2014: 1116-1124 - [i8]H. Brendan McMahan, Francesco Orabona:
Unconstrained Online Linear Learning in Hilbert Spaces: Minimax Algorithms and Normal Approximations. CoRR abs/1403.0628 (2014) - [i7]Francesco Orabona:
Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning. CoRR abs/1406.3816 (2014) - [i6]Ilja Kuzborskij, Barbara Caputo, Francesco Orabona:
Transfer Learning through Greedy Subset Selection. CoRR abs/1408.1292 (2014) - [i5]Ilja Kuzborskij, Francesco Orabona:
Learning by Transferring from Auxiliary Hypotheses. CoRR abs/1412.1619 (2014) - 2013
- [j7]Tatiana Tommasi, Francesco Orabona, Claudio Castellini, Barbara Caputo:
Improving Control of Dexterous Hand Prostheses Using Adaptive Learning. IEEE Trans. Robotics 29(1): 207-219 (2013) - [c33]Marco Fornoni, Barbara Caputo, Francesco Orabona:
Multiclass Latent Locally Linear Support Vector Machines. ACML 2013: 229-244 - [c32]Ilja Kuzborskij, Francesco Orabona, Barbara Caputo:
From N to N+1: Multiclass Transfer Incremental Learning. CVPR 2013: 3358-3365 - [c31]Ilja Kuzborskij, Francesco Orabona:
Stability and Hypothesis Transfer Learning. ICML (3) 2013: 942-950 - [c30]Samory Kpotufe, Francesco Orabona:
Regression-tree Tuning in a Streaming Setting. NIPS 2013: 1788-1796 - [c29]Francesco Orabona:
Dimension-Free Exponentiated Gradient. NIPS 2013: 1806-1814 - [i4]Francesco Orabona, Koby Crammer, Nicolò Cesa-Bianchi:
A Generalized Online Mirror Descent with Applications to Classification and Regression. CoRR abs/1304.2994 (2013) - [i3]Francesco Orabona, Tamir Hazan, Anand D. Sarwate, Tommi S. Jaakkola:
On Measure Concentration of Random Maximum A-Posteriori Perturbations. CoRR abs/1310.4227 (2013) - 2012
- [j6]Francesco Orabona, Jie Luo, Barbara Caputo:
Multi Kernel Learning with Online-Batch Optimization. J. Mach. Learn. Res. 13: 227-253 (2012) - [c28]Tatiana Tommasi, Francesco Orabona, Mohsen Kaboli, Barbara Caputo:
Leveraging over prior knowledge for online learning of visual categories. BMVC 2012: 1-11 - [c27]Claudio Gentile, Francesco Orabona:
On Multilabel Classification and Ranking with Partial Feedback. NIPS 2012: 1160-1168 - [c26]Francesco Orabona, Nicolò Cesa-Bianchi, Claudio Gentile:
Beyond Logarithmic Bounds in Online Learning. AISTATS 2012: 823-831 - [i2]Francesco Orabona, Andreas Argyriou, Nathan Srebro:
PRISMA: PRoximal Iterative SMoothing Algorithm. CoRR abs/1206.2372 (2012) - [i1]Claudio Gentile, Francesco Orabona:
On Multilabel Classification and Ranking with Partial Feedback. CoRR abs/1207.0166 (2012) - 2011
- [c25]Francesco Orabona, Jie Luo:
Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning. ICML 2011: 249-256 - [c24]Francesco Orabona, Nicolò Cesa-Bianchi:
Better Algorithms for Selective Sampling. ICML 2011: 433-440 - 2010
- [j5]Etienne Grossmann, José António Gaspar, Francesco Orabona:
Discrete camera calibration from pixel streams. Comput. Vis. Image Underst. 114(2): 198-209 (2010) - [j4]Francesco Orabona, Claudio Castellini, Barbara Caputo, Jie Luo, Giulio Sandini:
On-line independent support vector machines. Pattern Recognit. 43(4): 1402-1412 (2010) - [c23]Francesco Orabona, Marco Fornoni, Barbara Caputo, Nicolò Cesa-Bianchi:
OM-2: An online multi-class Multi-Kernel Learning algorithm Luo Jie. CVPR Workshops 2010: 43-50 - [c22]Francesco Orabona, Jie Luo, Barbara Caputo:
Online-batch strongly convex Multi Kernel Learning. CVPR 2010: 787-794 - [c21]Tatiana Tommasi, Francesco Orabona, Barbara Caputo:
Safety in numbers: Learning categories from few examples with multi model knowledge transfer. CVPR 2010: 3081-3088 - [c20]Jie Luo, Francesco Orabona:
Learning from Candidate Labeling Sets. NIPS 2010: 1504-1512 - [c19]Francesco Orabona, Koby Crammer:
New Adaptive Algorithms for Online Classification. NIPS 2010: 1840-1848 - [p1]Tatiana Tommasi, Francesco Orabona:
Idiap on Medical Image Classification. ImageCLEF 2010: 453-465
2000 – 2009
- 2009
- [j3]Francesco Orabona, Joseph Keshet, Barbara Caputo:
Bounded Kernel-Based Online Learning. J. Mach. Learn. Res. 10: 2643-2666 (2009) - [c18]Jie Luo, Francesco Orabona, Barbara Caputo:
An Online Framework for Learning Novel Concepts over Multiple Cues. ACCV (1) 2009: 269-280 - [c17]Nicolò Cesa-Bianchi, Claudio Gentile, Francesco Orabona:
Robust bounds for classification via selective sampling. ICML 2009: 121-128 - [c16]Francesco Orabona, Claudio Castellini, Barbara Caputo, Angelo Emanuele Fiorilla, Giulio Sandini:
Model adaptation with least-squares SVM for adaptive hand prosthetics. ICRA 2009: 2897-2903 - [c15]Muhammad Muneeb Ullah, Francesco Orabona, Barbara Caputo:
You live, you learn, you forget: Continuous learning of visual places with a forgetting mechanism. IROS 2009: 3154-3161 - 2008
- [j2]Tatiana Tommasi, Francesco Orabona, Barbara Caputo:
Discriminative cue integration for medical image annotation. Pattern Recognit. Lett. 29(15): 1996-2002 (2008) - [c14]Tatiana Tommasi, Francesco Orabona, Barbara Caputo:
An SVM Confidence-Based Approach to Medical Image Annotation. CLEF 2008: 696-703 - [c13]Tatiana Tommasi, Francesco Orabona, Barbara Caputo:
CLEF2008 Image Annotation Task: an SVM Confidence-Based Approach. CLEF (Working Notes) 2008 - [c12]Etienne Grossmann, José António Gaspar, Francesco Orabona:
Calibration from Statistical Properties of the Visual World. ECCV (4) 2008: 228-241 - [c11]Francesco Orabona, Joseph Keshet, Barbara Caputo:
The projectron: a bounded kernel-based Perceptron. ICML 2008: 720-727 - 2007
- [j1]Claudio Castellini, Francesco Orabona, Giorgio Metta, Giulio Sandini:
Internal models of reaching and grasping. Adv. Robotics 21(13): 1545-1564 (2007) - [c10]Francesco Orabona, Claudio Castellini:
Indoor Place Recognition using Online Independent Support Vector Machines. BMVC 2007: 1-10 - [c9]Tatiana Tommasi, Francesco Orabona, Barbara Caputo:
Cue Integration for Medical Image Annotation. CLEF 2007: 577-584 - [c8]Tatiana Tommasi, Francesco Orabona, Barbara Caputo:
CLEF2007: Image Annotation Task: an SVM-based Cue Integration Approach. CLEF (Working Notes) 2007 - [c7]Etienne Grossmann, Francesco Orabona, José António Gaspar:
Discrete camera calibration from the information distance between pixel streams. ICCV 2007: 1-8 - [c6]Francesco Orabona, Giorgio Metta, Giulio Sandini:
A Proto-object Based Visual Attention Model. WAPCV 2007: 198-215 - 2006
- [c5]Francesco Orabona, Giorgio Metta, Giulio Sandini:
Learning Association Fields from Natural Images. CVPR Workshops 2006: 174 - [c4]Milena Vurro, Giuseppe Baselli, Francesco Orabona, Giulio Sandini:
Simulation and Assessment of Bioinspired Visual Processing System for Epi-retinal Prostheses. EMBC 2006: 3278-3281 - 2005
- [c3]Lorenzo Natale, Francesco Orabona, Giorgio Metta, Giulio Sandini:
Exploring the world through grasping: a developmental approach. CIRA 2005: 559-565 - [c2]Francesco Orabona, Giorgio Metta, Giulio Sandini:
Object-based Visual Attention: a Model for a Behaving Robot. CVPR Workshops 2005: 89 - [c1]Lorenzo Natale, Francesco Orabona, Fabio Berton, Giorgio Metta, Giulio Sandini:
From sensorimotor development to object perception. Humanoids 2005: 226-231
Coauthor Index
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