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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

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

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

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

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

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

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

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

Imitation Learning
Vector Institute Reinforcement Learning Summer School 2018

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

Algorithms that learn to think on their feet
October 2015, UC Santa Cruz

Interpretese vs Translationese
August 2015, Shonan Workshop

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

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

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

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

Hierarchical Bayes Compiler
June 2008, ICML Workshop on Probabilistic Programming

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 twelve may, two thousand twenty four.