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Ariadna Quattoni Research Scientist at UPC. aquattoni/ at/ cs/upc/edu

Projects

Principal Investigator of INTERACT (Interactive Machine Learning for Compositional Models of Natural Language) a research project funded by the ERC (2020-2025).

Publications

[Cites (google-scholar)]

Articles

• Does Fine-tuning a Classifier Help in Low-budget Scenarios? Not Much, C. Gonzalez-Gutierrez, A. Primadhanty, F. Cazzaro and A. Quattoni. NAAACL 5th Workshop on Insights from Negative Results in NLP 2024, Mexico City, Mexico. [pdf]


• Leveraging the Structure of Pre-trained Embeddings to Minimize Annotation Effort, C. Gonzalez-Gutierrez and A. Quattoni. NAACL 2024, Mexico City, Mexico. [pdf]


• Align and Augment: Generative Data Augmentation for Compositional Generalization, F. Cazzaro, D. Locatelli and A. Quattoni. EACL 2024, St. Julians, Malta. [pdf]


• Entity Disambiguation on a Tight Labeling Budget, A. Primadhanty and A. Quattoni. EMNLP (Findings) 2023, Singapore. [pdf]


• Analyzing Text Representations by Measuring Task Alignment, C. Gonzalez-Gutierrez, A. Primadhanty, F. Cazzaro and A. Quattoni. ACL 2023, Toronto, USA. [pdf]


• Translate First Reorder Later: Leveraging Monotonicity in Semantic Parsing, F. Cazzaro, D. Locatelli, A. Quattoni and X.Carreras. EACL(Findings) 2023, Dubrovnik, HR. [pdf]


• Measuring Alignment Bias in Neural Seq2Seq Semantic Parsers, D. Locatelli and A. Quattoni. Proceedings of the Eleventh Joint Conference on Lexical and Computational Semantics (*SEM) 2022, Seattle, WA. [pdf] [github]


• Minimizing Annotation Effort via Max-Volume Spectral Sampling, A. Quattoni and X.Carreras. Findings of ACL: EMNLP 2021, Punta Cana, Dominican Republic. [pdf] [talk]


• A comparison between CNNs and WFAs for Sequence Classification, A. Quattoni and X.Carreras. Workshop SustaiNLP, EMNLP 2020. [pdf] [talk]


• Interpolated Spectral NGram Language Models, A. Quattoni and X.Carreras. ACL 2019. [pdf] [talk]


• Proceedings of the Workshop on Deep Learning and Formal Languages: Building Bridges, J. Eisner, M. Galle, J. Heinz, A. Quattoni, G. Rabusseau. Workshop on Deep Learning and Formal Languages: Building Bridges, ACL 2019. [pdf]


• Prepositional Phrase Attachment over Word Embedding Products, P. Madhyastha, C. Carreras, A. Quattoni. IWPT 2017. [pdf]


• A Maximum Matching Algorithm for Basis Selection in Spectral Learning, A. Quattoni, X. Carreras, M. Galle. AISTATS 2017. [pdf]


• InToEventS: An Interactive Toolkit for Discovering and Building Event Schemas, G. Ferrero, A. Primadhanty, A. Quattoni. EACL 2017. [pdf]


• Results of the sequence prediction challenge (spice): a competition on learning the next symbol in a sequence, B. Balle, R. Eyraud, F. Luque, A. Quattoni, S. Verwer. ICGI 2017. [pdf]


• Structured Prediction with Output Embeddings for Semantic Image Annotation, A. Quattoni, A. Ramisa, P. Madhyastha, E. Simo-Serra, F. Moreno-Noguer. NAACL 2016. [pdf]


• Semantic tuples for evaluation of image sentence generation, L. Ellebracht, A. Ramisa, P. Madhyastha, J. Cordero-Rama, F. Moreno-Noguer, A. Quattoni. Worshop on Vision and Language 2015. [pdf]


• Low-Rank Regularization for Sparse Conjunctive Feature Spaces: An Application to Named Entity Classification, A. Primadhanty, X. Carreras, A. Quattoni. ACL 2015. [pdf]


• Spectral Learning of Weighted Automata: A Forward-Backward Perspective, B. Balle, X. Carreras, F. Luque, A. Quattoni. MLJ 2014, Special Issue on Grammatical Inference. [pdf]


• Tailoring Word Embeddings For Bilexicl Predictions: An Experimental Comparison, P. Madhyastha, C. Carreras, A. Quattoni. ICLR 2014. [pdf]


• Spectral Regularization for Max-Margin Sequence Tagging, A. Quattoni, B. Balle, C. Carreras, A.Globerson. ICML 2014. [pdf]


• Learning Task-Specific Bilexical Embeddings, P. Madhyastha, C. Carreras, A. Quattoni. COLING 2014. [pdf]


• Unsupervised Learning of Finite State Transducers, R. Bailly, X. Carreras, A. Quattoni. NIPS 2013. [pdf]


• Unsupervised Spectral Learning of WCFG as Low-rankMatrix Completion, R. Bailly, X. Carreras, F. Luque, A. Quattoni. EMNLP 2013. [pdf]


• Spectral Learning of Sequence Taggers over Continuos Sequences, A. Recasens, A. Quattoni. ECML 2013. [pdf]


• A Joint Model for 2D and 3D Pose Estimation from a Single Image, E. Simo-Serra, A. Quattoni, F. Moreno-Noguer, C. Torras.CVPR 2013. [pdf]


• Local Loss Optimization in Operator Models: A New Insight into Spectral Learning, B. Balle, A.Quattoni, X. Carreras. ICML 2012. [pdf]


• Spectral Learning for Non-Deterministic Dependency Parsing, F. Luque, A. Quattoni, B. Balle, X. Carreras. EACL 2012, Best Paper Award. [pdf]


• A Latent Variable Ranking Model for Content-based Retrieval, A. Quattoni, X. Carreras, A. Torralba. ECIR 2012. [pdf]


• A Spectral Learning Algorithm for Finite State Transducers, B. Balle, A. Quattoni, X. Carreras. ECML 2011. [pdf]


• An Efficient Projection for L1,Infinity Regularization, A. Quattoni, X. Carreras, M. Collins, T. Darrell. ICML 2009. [pdf]


• Recognizing Indoor Scenes, A. Quattoni, A. Torralba. CVPR 2009. [pdf]


• Transfer Learning for Image Classification with Sparse Prototype Representations, A. Quattoni, M. Collins, T. Darrell. CVPR 2008. [pdf]


• Learning Visual Representations using Images with Captions, A. Quattoni, M. Collins, T. Darrell. CVPR 2007. [pdf]


• Hidden-state Conditional Random Fields, A. Quattoni, S. Wang, L.P. Morency, M. Collins, and T. Darrell. IEEE PAMI, 2007 [pdf]


• Latent-Dynamic Discriminative Models for Continuous Gesture Recognition, L.P. Morency, A. Quattoni, T. Darrell. CVPR 2007. [pdf]


• Hidden Conditional Random Fields for Gesture Recognition, S.Wang, A. Quattoni, L.P. Morency, D. Demirdjian, T. Darrell. CVPR 2006. [pdf]


• Incorporating Semantic Constraints into a Discriminative Categorization and Labeling Model, A. Quattoni, M. Collins, T. Darrell. Workshop on Semantic Knowledge in Vision, ICCV, 2005. [pdf]


• Conditional Random Fields for Object Recognition, A. Quattoni, M. Collins, T. Darrell. NIPS 2004. [pdf]

Technical Reports

• Spectral Learning of Transducers Over Continuous Sequences, A. Recasens, A. Quattoni, UPC TR 2012 .


• Transferring Nonlinear Representations using Gaussian Processes with a Shared Latent Space, R. Urtasun, A. Quattoni, N. Lawrence, T. Darrell, MIT TR 2008 . [pdf]


• A Projected Subgradient Method for Scalable Multi-Task Learning, A. Quattoni, X. Carreras, M. Collins, T. Darrel, MIT TR 2008 2008. [pdf]

Thesis

• Transfer Learning Algorithms for Image Classification, Phd Thesis, Massachussetts Institure of Technology 2009. [pdf]


• Latent Conditional Random Fields for Object Recognition, Master Thesis, Massachussetts Institute of Technology 2005. [pdf]

Software

• HCRF: Hidden Conditional Random Fields Library.


• L1InfProjection : L1Inf Projection matlab code.

Talks

• Latent Variable Models for Content-based Image Retrieval and Structure Prediction, UK Computer Vision Student Workshop - BMVC 2012 (Keynote) , [pdf] [video]


• An Automata Theory Perspective on Spectral Learning: Hankel Matrix Factorizations , NIPS Workshop on Spectral Learning - NIPS 2012 (Invited Speaker) , [pdf]


• Transfer Learning Algorithms for Image Classification, Phd Thesis Defense, [pdf]


• An Efficient Projection for L1,Infinity Regularization, ICML 2009, [pdf] [video]


• Tutorial on Conditional Random Fields, LARCA Seminar 2009, [pdf]

Last updated: July 2020

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