Valentina Zantedeschi

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 37

Top Venues

CoRR

AISTATS

ICLR

ICML

University of Lyon, France (PHD)

Education History

University of Lyon, France

PHD

Publications

Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series. ICLR (2024)
Gaurav Sahu, Abhay Puri, Juan A. Rodriguez, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vázquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam Hadj Laradji
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. CoRR (2024)
João Monteiro, Étienne Marcotte, Pierre-André Noël, Valentina Zantedeschi, David Vázquez, Nicolas Chapados, Christopher Pal, Perouz Taslakian
XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference. CoRR (2024)
Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. AISTATS (2024)
João Monteiro, Pierre-André Noël, Étienne Marcotte, Sai Rajeswar, Valentina Zantedeschi, David Vázquez, Nicolas Chapados, Christopher Pal, Perouz Taslakian
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content. CoRR (2024)
Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. CoRR (2024)
Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series. CoRR (2023)
Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt J. Kusner, Vlad Niculae
DAG Learning on the Permutahedron. ICLR (2023)
Stephanie Long, Alexandre Piché, Valentina Zantedeschi, Tibor Schuster, Alexandre Drouin
Causal Discovery with Language Models as Imperfect Experts. CoRR (2023)
Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt J. Kusner, Vlad Niculae
DAG Learning on the Permutahedron. CoRR (2023)
Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin, Nicolas Chapados
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts. CoRR (2023)
Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin, Nicolas Chapados
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts. ICML (2023)
Issam H. Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vázquez, Christopher Pal, Alexandre Drouin
Capture the Flag: Uncovering Data Insights with Large Language Models. CoRR (2023)
Felix Biggs, Valentina Zantedeschi, Benjamin Guedj
On Margins and Generalisation for Voting Classifiers. CoRR (2022)
Nicolas Traut, Katja Heuer, Guillaume Lemaître, Anita Beggiato, David Germanaud, Monique Elmaleh, Alban Bethegnies, Laurent Bonnasse-Gahot, Weidong Cai, Stanislas Chambon, Freddy Cliquet, Ayoub Ghriss, Nicolas Guigui, Amicie de Pierrefeu, Meng Wang, Valentina Zantedeschi, Alexandre Boucaud, Joris Van den Bossche, Balázs Kégl, Richard Delorme, Thomas Bourgeron, Roberto Toro, Gaël Varoquaux
Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery. NeuroImage 255 (2022)
Andrew J. Wren, Pasquale Minervini, Luca Franceschi, Valentina Zantedeschi
Learning Discrete Directed Acyclic Graphs via Backpropagation. CoRR (2022)
Felix Biggs, Valentina Zantedeschi, Benjamin Guedj
On Margins and Generalisation for Voting Classifiers. NeurIPS (2022)
Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Alfredo Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski
RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery. AAAI (2021)
Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. NeurIPS (2021)
Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. CoRR (2021)
Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae
Learning Binary Decision Trees by Argmin Differentiation. ICML (2021)
Vít Ruzicka, Anna Vaughan, Daniele De Martini, James Fulton, Valentina Salvatelli, Chris Bridges, Gonzalo Mateo-Garcia, Valentina Zantedeschi
Unsupervised Change Detection of Extreme Events Using ML On-Board. CoRR (2021)
Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Freddie Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski
RainBench: Towards Global Precipitation Forecasting from Satellite Imagery. CoRR (2020)
Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs. AISTATS (2020)
Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae
Learning Binary Trees via Sparse Relaxation. CoRR (2020)
Léo Gautheron, Pascal Germain, Amaury Habrard, Guillaume Metzler, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting. ECML/PKDD (3) (2020)
Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi
Communication-Efficient and Decentralized Multi-Task Boosting while Learning the Collaboration Graph. CoRR (2019)
Valentina Zantedeschi, Fabrizio Falasca, Alyson Douglas, Richard Strange, Matt J. Kusner, Duncan Watson-Parris
Cumulo: A Dataset for Learning Cloud Classes. CoRR (2019)
Léo Gautheron, Pascal Germain, Amaury Habrard, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting. CoRR (2019)
Maria-Irina Nicolae, Mathieu Sinn, Tran Ngoc Minh, Ambrish Rawat, Martin Wistuba, Valentina Zantedeschi, Ian M. Molloy, Benjamin Edwards
Adversarial Robustness Toolbox v0.2.2. CoRR (2018)
Valentina Zantedeschi, Rémi Emonet, Marc Sebban
Fast and Provably Effective Multi-view Classification with Landmark-Based SVM. ECML/PKDD (2) (2018)
Valentina Zantedeschi, Rémi Emonet, Marc Sebban
-SVMs: Landmarks-based Linear Local Support Vectors Machines. CoRR (2017)
Valentina Zantedeschi, Maria-Irina Nicolae, Ambrish Rawat
Efficient Defenses Against Adversarial Attacks. AISec@CCS (2017)
Valentina Zantedeschi, Maria-Irina Nicolae, Ambrish Rawat
Efficient Defenses Against Adversarial Attacks. CoRR (2017)
Valentina Zantedeschi, Rémi Emonet, Marc Sebban
beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data. NIPS (2016)
Valentina Zantedeschi, Rémi Emonet, Marc Sebban
Lipschitz Continuity of Mahalanobis Distances and Bilinear Forms. CoRR (2016)
Valentina Zantedeschi, Rémi Emonet, Marc Sebban
Metric Learning as Convex Combinations of Local Models with Generalization Guarantees. CVPR (2016)

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Publication Activity (10 Years)

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Valentina Zantedeschi