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ORCIDTobias Schnabel
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Books and Theses
- 2018
[b1]Tobias Schnabel:
Improving Machine Learning Beyond the Algorithm. Cornell University, USA, 2018
Journal Articles
- 2024
- [j4]Jacopo Tagliabue
, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia:
Author Correction: A challenge for rounded evaluation of recommender systems. Nat. Mac. Intell. 6(3): 368 (2024) - 2023
- [j3]Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia:
A challenge for rounded evaluation of recommender systems. Nat. Mac. Intell. 5(2): 181-182 (2023) - 2022
- [j2]Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst:
SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization. Trans. Assoc. Comput. Linguistics 10: 163-177 (2022) - 2014
- [j1]Tobias Schnabel, Hinrich Schütze:
FLORS: Fast and Simple Domain Adaptation for Part-of-Speech Tagging. Trans. Assoc. Comput. Linguistics 2: 15-26 (2014)
Conference and Workshop Papers
- 2023
- [c23]Yushun Dong, Jundong Li, Tobias Schnabel:
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? SIGIR 2023: 942-952 - [c22]Da Xu, Tobias Schnabel, Xiquan Cui, Sarah Dean, Aniket Anand Deshmukh, Bo Yang, Shipeng Yu:
Foreword for Workshop on Decision Making for Information Retrieval and Recommender Systems. WWW (Companion Volume) 2023: 920 - 2022
- [c21]Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia:
EvalRS: a rounded evaluation of recommender systems. CIKM Workshops 2022 - [c20]Quan Ze Chen, Tobias Schnabel, Besmira Nushi, Saleema Amershi:
HINT: Integration Testing for AI-based features with Humans in the Loop. IUI 2022: 549-565 - 2021
- [c19]Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst:
Keep It Simple: Unsupervised Simplification of Multi-Paragraph Text. ACL/IJCNLP (1) 2021: 6365-6378 - [c18]Longqi Yang, Tobias Schnabel, Paul N. Bennett, Susan T. Dumais:
Local Factor Models for Large-Scale Inductive Recommendation. RecSys 2021: 252-262 - 2020
- [c17]Tobias Schnabel, Paul N. Bennett:
Debiasing Item-to-Item Recommendations With Small Annotated Datasets. RecSys 2020: 73-81 - [c16]Tobias Schnabel, Gonzalo A. Ramos, Saleema Amershi:
"Who doesn't like dinosaurs?" Finding and Eliciting Richer Preferences for Recommendation. RecSys 2020: 398-407 - [c15]Tobias Schnabel, Saleema Amershi, Paul N. Bennett, Peter Bailey, Thorsten Joachims:
The Impact of More Transparent Interfaces on Behavior in Personalized Recommendation. SIGIR 2020: 991-1000 - 2019
- [c14]Andrew Bennett, Nathan Kallus, Tobias Schnabel:
Deep Generalized Method of Moments for Instrumental Variable Analysis. NeurIPS 2019: 3559-3569 - [c13]Tobias Schnabel, Paul N. Bennett, Thorsten Joachims:
Shaping Feedback Data in Recommender Systems with Interventions Based on Information Foraging Theory. WSDM 2019: 546-554 - 2018
- [c12]Thorsten Joachims, Adith Swaminathan, Tobias Schnabel:
Unbiased Learning-to-Rank with Biased Feedback. IJCAI 2018: 5284-5288 - [c11]Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims:
Short-Term Satisfaction and Long-Term Coverage: Understanding How Users Tolerate Algorithmic Exploration. WSDM 2018: 513-521 - 2017
- [c10]Aman Agarwal, Soumya Basu, Tobias Schnabel, Thorsten Joachims:
Effective Evaluation Using Logged Bandit Feedback from Multiple Loggers. KDD 2017: 687-696 - [c9]Thorsten Joachims, Adith Swaminathan, Tobias Schnabel:
Unbiased Learning-to-Rank with Biased Feedback. WSDM 2017: 781-789 - 2016
- [c8]Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims:
Recommendations as Treatments: Debiasing Learning and Evaluation. ICML 2016: 1670-1679 - [c7]Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims:
Unbiased Comparative Evaluation of Ranking Functions. ICTIR 2016: 109-118 - [c6]Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims:
Using Shortlists to Support Decision Making and Improve Recommender System Performance. WWW 2016: 987-997 - 2015
- [c5]Tobias Schnabel, Igor Labutov, David M. Mimno, Thorsten Joachims:
Evaluation methods for unsupervised word embeddings. EMNLP 2015: 298-307 - [c4]Wenpeng Yin, Tobias Schnabel, Hinrich Schütze:
Online Updating of Word Representations for Part-of-Speech Tagging. EMNLP 2015: 1329-1334 - [c3]Tobias Schnabel, Adith Swaminathan, Thorsten Joachims:
Unbiased Ranking Evaluation on a Budget. WWW (Companion Volume) 2015: 935-937 - 2013
- [c2]Karthik Raman, Thorsten Joachims, Pannaga Shivaswamy, Tobias Schnabel:
Stable Coactive Learning via Perturbation. ICML (3) 2013: 837-845 - [c1]Tobias Schnabel, Hinrich Schütze:
Towards Robust Cross-Domain Domain Adaptation for Part-of-Speech Tagging. IJCNLP 2013: 198-206
Informal and Other Publications
- 2024
- [i19]Tobias Schnabel, Jennifer Neville:
Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. CoRR abs/2404.02319 (2024) - [i18]Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan:
On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots. CoRR abs/2406.01633 (2024) - 2023
- [i17]Yushun Dong, Jundong Li, Tobias Schnabel:
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? CoRR abs/2305.01801 (2023) - 2022
- [i16]Mengyue Hang, Tobias Schnabel, Longqi Yang, Jennifer Neville:
Lightweight Compositional Embeddings for Incremental Streaming Recommendation. CoRR abs/2202.02427 (2022) - [i15]Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia:
EvalRS: a Rounded Evaluation of Recommender Systems. CoRR abs/2207.05772 (2022) - [i14]Tobias Schnabel:
Where Do We Go From Here? Guidelines For Offline Recommender Evaluation. CoRR abs/2211.01261 (2022) - [i13]Tobias Schnabel, Mengting Wan, Longqi Yang:
Situating Recommender Systems in Practice: Towards Inductive Learning and Incremental Updates. CoRR abs/2211.06365 (2022) - 2021
- [i12]Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst:
Keep it Simple: Unsupervised Simplification of Multi-Paragraph Text. CoRR abs/2107.03444 (2021) - [i11]Philippe Laban, Tobias Schnabel, Paul N. Bennett, Marti A. Hearst:
SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization. CoRR abs/2111.09525 (2021) - 2019
- [i10]Andrew Bennett, Nathan Kallus, Tobias Schnabel:
Deep Generalized Method of Moments for Instrumental Variable Analysis. CoRR abs/1905.12495 (2019) - 2018
- [i9]Tobias Schnabel, Paul N. Bennett, Thorsten Joachims:
Improving Recommender Systems Beyond the Algorithm. CoRR abs/1802.07578 (2018) - 2017
- [i8]Aman Agarwal, Soumya Basu, Tobias Schnabel, Thorsten Joachims:
Effective Evaluation using Logged Bandit Feedback from Multiple Loggers. CoRR abs/1703.06180 (2017) - [i7]Pantelis P. Analytis, Tobias Schnabel, Stefan M. Herzog, Daniel Barkoczi, Thorsten Joachims:
A preference elicitation interface for collecting dense recommender datasets with rich user information. CoRR abs/1706.08184 (2017) - 2016
- [i6]Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims:
Recommendations as Treatments: Debiasing Learning and Evaluation. CoRR abs/1602.05352 (2016) - [i5]Wenpeng Yin, Tobias Schnabel, Hinrich Schütze:
Online Updating of Word Representations for Part-of-Speech Tagging. CoRR abs/1604.00502 (2016) - [i4]Tobias Schnabel, Adith Swaminathan, Peter I. Frazier, Thorsten Joachims:
Unbiased Comparative Evaluation of Ranking Functions. CoRR abs/1604.07209 (2016) - [i3]Thorsten Joachims, Adith Swaminathan, Tobias Schnabel:
Unbiased Learning-to-Rank with Biased Feedback. CoRR abs/1608.04468 (2016) - 2015
- [i2]Tobias Schnabel, Paul N. Bennett, Susan T. Dumais, Thorsten Joachims:
Using Shortlists to Support Decision Making and Improve Recommender System Performance. CoRR abs/1510.07545 (2015) - [i1]S. Sathiya Keerthi, Tobias Schnabel, Rajiv Khanna:
Towards a Better Understanding of Predict and Count Models. CoRR abs/1511.02024 (2015)
Coauthor Index
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