Folgen
Tobias Schnabel
Tobias Schnabel
Researcher, Microsoft
Bestätigte E-Mail-Adresse bei cornell.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Evaluation methods for unsupervised word embeddings
T Schnabel, I Labutov, D Mimno, T Joachims
Proceedings of the 2015 conference on empirical methods in natural language …, 2015
6312015
Recommendations as treatments: Debiasing learning and evaluation
T Schnabel, A Swaminathan, A Singh, N Chandak, T Joachims
In Proceedings of The International Conference on Machine Learning (ICML), 2016
3502016
Unbiased learning-to-rank with biased feedback
T Joachims, A Swaminathan, T Schnabel
Proceedings of the tenth ACM international conference on web search and data …, 2017
3482017
Flors: Fast and simple domain adaptation for part-of-speech tagging
T Schnabel, H Schütze
Transactions of the Association for Computational Linguistics 2, 15-26, 2014
672014
Deep generalized method of moments for instrumental variable analysis
A Bennett, N Kallus, T Schnabel
Advances in neural information processing systems 32, 2019
562019
Effective evaluation using logged bandit feedback from multiple loggers
A Agarwal, S Basu, T Schnabel, T Joachims
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017
482017
Using shortlists to support decision making and improve recommender system performance
T Schnabel, PN Bennett, ST Dumais, T Joachims
Proceedings of the 25th International Conference on World Wide Web, 987-997, 2016
412016
Short-term satisfaction and long-term coverage: Understanding how users tolerate algorithmic exploration
T Schnabel, PN Bennett, ST Dumais, T Joachims
Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018
372018
Stable coactive learning via perturbation
K Raman, T Joachims, P Shivaswamy, T Schnabel
International conference on machine learning, 837-845, 2013
252013
Unbiased comparative evaluation of ranking functions
T Schnabel, A Swaminathan, PI Frazier, T Joachims
Proceedings of the 2016 ACM International Conference on the Theory of …, 2016
242016
Online updating of word representations for part-of-speech tagging
W Yin, T Schnabel, H Schütze
arXiv preprint arXiv:1604.00502, 2016
182016
SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization
P Laban, T Schnabel, PN Bennett, MA Hearst
arXiv preprint arXiv:2111.09525, 2021
142021
Shaping feedback data in recommender systems with interventions based on information foraging theory
T Schnabel, PN Bennett, T Joachims
Proceedings of the Twelfth ACM International Conference on Web Search and …, 2019
142019
Improving recommender systems beyond the algorithm
T Schnabel, PN Bennett, T Joachims
arXiv preprint arXiv:1802.07578, 2018
142018
Towards robust cross-domain domain adaptation for part-of-speech tagging
T Schnabel
142013
Keep it simple: Unsupervised simplification of multi-paragraph text
P Laban, T Schnabel, P Bennett, MA Hearst
arXiv preprint arXiv:2107.03444, 2021
92021
Debiasing item-to-item recommendations with small annotated datasets
T Schnabel, PN Bennett
Fourteenth ACM Conference on Recommender Systems, 73-81, 2020
82020
Towards a better understanding of predict and count models
SS Keerthi, T Schnabel, R Khanna
arXiv preprint arXiv:1511.02024, 2015
82015
The impact of more transparent interfaces on behavior in personalized recommendation
T Schnabel, S Amershi, PN Bennett, P Bailey, T Joachims
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
62020
“Who doesn’t like dinosaurs?” Finding and Eliciting Richer Preferences for Recommendation
T Schnabel, G Ramos, S Amershi
Fourteenth ACM Conference on Recommender Systems, 398-407, 2020
52020
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20