Παρακολούθηση
Eleni Triantafillou
Eleni Triantafillou
Google DeepMind
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα google.com - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
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Meta-learning for semi-supervised few-shot classification
M Ren, E Triantafillou, S Ravi, J Snell, K Swersky, JB Tenenbaum, ...
arXiv preprint arXiv:1803.00676, 2018
17222018
Meta-dataset: A dataset of datasets for learning to learn from few examples
E Triantafillou, T Zhu, V Dumoulin, P Lamblin, U Evci, K Xu, R Goroshin, ...
arXiv preprint arXiv:1903.03096, 2019
7612019
Few-shot learning through an information retrieval lens
E Triantafillou, R Zemel, R Urtasun
Advances in neural information processing systems 30, 2017
2862017
Towards unbounded machine unlearning
M Kurmanji, P Triantafillou, J Hayes, E Triantafillou
Advances in neural information processing systems 36, 2024
1562024
Non-deterministic planning with temporally extended goals: LTL over finite and infinite traces
A Camacho, E Triantafillou, C Muise, J Baier, S McIlraith
Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017
1202017
Learning a universal template for few-shot dataset generalization
E Triantafillou, H Larochelle, R Zemel, V Dumoulin
International conference on machine learning, 10424-10433, 2021
1142021
Inexact unlearning needs more careful evaluations to avoid a false sense of privacy
J Hayes, I Shumailov, E Triantafillou, A Khalifa, N Papernot
arXiv preprint arXiv:2403.01218, 2024
242024
Ununlearning: Unlearning is not sufficient for content regulation in advanced generative ai
I Shumailov, J Hayes, E Triantafillou, G Ortiz-Jimenez, N Papernot, ...
arXiv preprint arXiv:2407.00106, 2024
192024
Towards generalizable sentence embeddings
E Triantafillou, J Kiros, R Urtasun, R Zemel
Proceedings of the 1st Workshop on Representation Learning for NLP, 239-248, 2016
192016
In search for a generalizable method for source free domain adaptation
M Boudiaf, T Denton, B Van Merriënboer, V Dumoulin, E Triantafillou
International Conference on Machine Learning, 2914-2931, 2023
182023
Few-shot out-of-distribution detection
K Wang, P Vicol, E Triantafillou, R Zemel
ICML Workshop on Uncertainty and Robustness in Deep Learning 6 (7), 8, 2020
132020
Meta-learning for semi-supervised few-shot classification
E Triantafillou, H Larochelle, J Snell, J Tenenbaum, KJ Swersky, M Ren, ...
International Conference on Learning Representations, 2018
122018
A unifying framework for planning with LTL and regular expressions
E Triantafillou, J Baier, S McIlraith
MOCHAP@ ICAPS, 23-31, 2015
122015
Flexible few-shot learning with contextual similarity
M Ren, E Triantafillou, KC Wang, J Lucas, J Snell, X Pitkow, AS Tolias, ...
arXiv preprint arXiv:2012.05895, 1, 2020
102020
Non-Deterministic Planning with Temporally Extended Goals: Completing the Story for Finite and Infinite LTL (Amended Version).
A Camacho, E Triantafillou, CJ Muise, JA Baier, SA McIlraith
KnowProS@ IJCAI, 2016
102016
Birds, bats and beyond: Evaluating generalization in bioacoustics models
B Van Merriënboer, J Hamer, V Dumoulin, E Triantafillou, T Denton
Frontiers in Bird Science 3, 1369756, 2024
82024
What makes unlearning hard and what to do about it
K Zhao, M Kurmanji, GO Bărbulescu, E Triantafillou, P Triantafillou
arXiv preprint arXiv:2406.01257, 2024
82024
Machine unlearning in learned databases: An experimental analysis
M Kurmanji, E Triantafillou, P Triantafillou
Proceedings of the ACM on Management of Data 2 (1), 1-26, 2024
82024
Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition
E Triantafillou, P Kairouz, F Pedregosa, J Hayes, M Kurmanji, K Zhao, ...
arXiv preprint arXiv:2406.09073, 2024
72024
BIRB: A Generalization Benchmark for Information Retrieval in Bioacoustics
J Hamer, E Triantafillou, B van Merrienboer, S Kahl, H Klinck, T Denton, ...
arXiv preprint arXiv:2312.07439, 2023
72023
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