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Talks/tutorials/panels/podcast for which I have slides or videos:

AI UK: Doing better in data science – from algorithmic fairness to diversity
Anjali Mazumder, Shakir Mohamed, Danielle Belgrave, Maria De-Arteaga, and Hal Daumé III
The Alan Turing Institute AI UK Roadmap, March 2021
[Video]

Coded Bias Panel Discussion at the University of Maryland
Margrét Bjarnadóttir, Nicol Turner Lee, Deborah Raji, Adam Wenchel, and Hal Daumé III (moderator)
March, 2021
[Video]

Responsible AI Systems and Experiences
Abolfazl Asudeh (moderator), Hal Daumé III, Golnoosh Farnadi, Bernease Herman, Bill Howe (moderator), Yuval Moskovitch, Katie Shilton, and Jenn Wortman Vaughan
Panel at VLDB 2021
[Video]

Tech Ethics in a Changing World
Catherine Bannister, Mary Lacity, Cindy Moehring, and Hal Daumé III
Northwest Arkansas Tech Summit, 2021
[Video]

Language (Technology) Is Power: Exploring the Inherent Complexity of NLP Systems
Hal Daumé III and Sam Charrington (host)
TWIML AI Podcast, 2020
[Video]

The Meaning and Measurement of Bias: Lessons from NLP
Abigail Z. Jacobs, Su Lin Blodgett, Solon Barocas, Hal Daumé III, and Hanna Wallach.
FAccT 2020
[Site] [Video]

(Meta-)Learning from Interaction
NYU Machine Learning Reading Group 2019
[PDF] [ODP]

Out of Order! Flexible neural language generation
NAACL 2019 NeuralGen Workshop
[PPTx]

Beyond demonstrations: Learning behavior from higher-level supervision
ICML 2019 I3 Workshop
[PPTX]

Imitation Learning
Vector Institute Reinforcement Learning Summer School 2018
[PDF] [ODP]

Learning language through interaction
December 2016, Georgetown, Amazon, USC, GATech, UW, ...
[PDF] [ODP] [Video]

Bias in AI
November 2016, UMD MCWIC Diversity Summit
[PDF] [ODP] [PPTx (exported)] [Blog Post]

Locally optimal learning to search and distant supervision
December 2015, UMD CS Research Seminar
[PDF] [ODP] [Video]

Imitation learning and recurrent neural networks mashup
December 2015, CIFAR NCAP Workshop
[PDF] [ODP]

Algorithms that learn to think on their feet
October 2015, UC Santa Cruz
[PDF] [ODP]

Interpretese vs Translationese
August 2015, Shonan Workshop
[PDF] [ODP]

Advances in Structured Prediction
June 2015, ICML Tutorial (with John Lanford)
[PDF Part 1] [ODP Part 1] [PDF Part 2] [Video]

Hands-on Learning to Search for Joint Prediction
May 2015, NAACL Tutorial
[PDF Part 1] [PDF Part 2] [PDF Part 3] [Video]

Algorithms that learn to think on their feet
May 2015, Invited Talk at ICLR
[PDF] [ODP] [Video]

A picture is worth 13.6 words (on average)
February 2015, MSR NY Tea Talk
[PDF] [ODP]

Domain adaptation: the problem of new labels
December 2014, NeurIPS workshop on Transfer and Multitask Learning
[PDF] [ODP]

Efficiently programming efficient structured prediction
November 2014, UMD CLIP Seminar
[PDF] [ODP] [Video] [Notebook]

Algorithms that learn to think on their feet
October 2014, Columbia University Data Science Institute
[PDF] [ODP] [Video]

Understanding and adapting statistical models: an exploration in language
May 2014, University of Toronto
[PDF] [ODP]

Better! Faster! Stronger*! Learning to balance accuracy and efficiency when predicting linguistic structures
June 2013, ICML Workshop on Inferning
[PDF] [ODP] [Video]

Domain Adaptation
June 2010, ICML Tutorial
[PDF] [PPT]

Hierarchical Bayes Compiler
June 2008, ICML Workshop on Probabilistic Programming
[Video]



credits: design and font inspired by Seth Able's LoRD, some images converted to ANSI using ManyTools, original drawing of me by anonymous.
last updated on nine june, two thousand twenty two.