8 citations · 12 across the 4 of their papers we have counts for
6 papers
Active Imitation Learning from Multiple Non-Deterministic Teachers: Formulation, Challenges, and Algorithms
Khanh Nguyen, Hal Daumé
We formulate the problem of learning to imitate multiple, non-deterministic teachers with minimal interaction cost. Rather than learning a specific policy as in standard imitation…
Language (Technology) is Power: A Critical Survey of "Bias" in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé +1
We survey 146 papers analyzing "bias" in NLP systems, finding that their motivations are often vague, inconsistent, and lacking in normative reasoning, despite the fact that analyz…
Operationalizing the Legal Principle of Data Minimization for Personalization
Asia J. Biega, Peter Potash, Hal Daumé +2
Article 5(1)(c) of the European Union's General Data Protection Regulation (GDPR) requires that "personal data shall be [...] adequate, relevant, and limited to what is necessary i…
Active Imitation Learning with Noisy Guidance
Kianté Brantley, Amr Sharaf, Hal Daumé
Imitation learning algorithms provide state-of-the-art results on many structured prediction tasks by learning near-optimal search policies. Such algorithms assume training-time ac…
Meta-Learning for Few-Shot NMT Adaptation
Amr Sharaf, Hany Hassan, Hal Daumé
We present META-MT, a meta-learning approach to adapt Neural Machine Translation (NMT) systems in a few-shot setting. META-MT provides a new approach to make NMT models easily adap…
Weight of Evidence as a Basis for Human-Oriented Explanations
David Alvarez-Melis, Hal Daumé, Jennifer Wortman Vaughan +1
Interpretability is an elusive but highly sought-after characteristic of modern machine learning methods. Recent work has focused on interpretability via , w…