EPSRC Centre for Doctoral Training in Data Science. Training PhDs in machine learning, databases, stats+opt, & analysis of unstructured data at Edinburgh Uni
Edinburgh, Scotland
Joined November 2013
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Congratulations Tom! The hard work pays off!
My PhD thesis "Modelling Cross-lingual Transfer For Semantic Parsing" is finally submitted! 🎉🎉🎉 #NLProc
CDT in Data Science retweeted
Poster sessions are happening today! 11:40-1:20 and 5:00-5:30 today in room 208-210.
Come chat transfer learning for Gaussian processes and Bayesian optimisation 🌸
Excited to be in 🎊New Orleans🎊 this week for #NeurIPS2023! Ping me to chat Bayesian optimisation, transfer learning or ML and climate. Or if you know any good runs nearby!
And if you're interested in the above topics you should stop by our poster on Saturday!
CDT in Data Science retweeted
Do you love cross-lingual transfer?
Are you interested in putting latent variables everywhere you can?
Desperately searching for applied optimal transport research?
Come to my poster 16:00 in East Foyer! #EMNLP2023
virtual2023.emnlp.org/paper_…
w/ @tomhosking + Mirella Lapata
CDT in Data Science retweeted
🚨New TACL paper 🚨
Can we use explicit latent variable alignment for cross-lingual transfer? Minotaur uses optimal transport for explicit alignment across languages.
w/ @tomhosking, Mirella Lapata.
To be presented @emnlpmeeting + @mrl2023 in-person 🇸🇬
doi.org/10.1162/tacl_a_00611
CDT in Data Science retweeted
Excited for the poster session this afternoon at @automl_conf! I'll be talking about hyperparameter optimisation for increasing data set sizes and learning between tasks.
Work with Huibin Shen, @FrancoisAubet, David Salinas and @kleiaaro #AutoML23
Finding yourself repeatedly training your ML model because you’ve collected more data? Not sure what to do with the hyperparameters? We investigated for you!
Check out the paper arxiv.org/abs/2306.16916 with the wonderful Huibin Shen, @FrancoisAubet, David Salinas and @kleiaaro
CDT in Data Science retweeted
I'm really happy to share the news that Meta-Calibration has been accepted to TMLR! Meta-Calibration uses meta-learning as a new way to optimise for uncertainty calibration of neural networks. I've had a very positive experience with TMLR and certainly recommend submitting there!
Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error
Ondrej Bohdal, Yongxin Yang, Timothy Hospedales.
Action editor: Yingzhen Li.
openreview.net/forum?id=R2hU…
#calibration #prediction #optimise
CDT in Data Science retweeted
Life update: I have passed my PhD defense (@alexandrabirch1 and @licwu were excellent examiners), and moved to New York City!
Many thanks to everyone who made the PhD experience so fun, especially my CDT cohort, collaborators, and supervisor @driainmurray
CDT in Data Science retweeted
I'm very excited to be in Seoul to give a talk and present a poster about our CVPR'23 Meta Omnium paper at the Hyundai Vision Conference! Feel free to take a look at the poster and also a few photos from this great city! Meta Omnium website: edi-meta-learning.github.io/…
CDT in Data Science retweeted
Interested in what could be the long-term implications of deploying too many AI systems that are not fair? You can learn more in our paper - we've updated it on arXiv with the version that will appear soon in the proceedings of the Stanford Existential Risk Conference!
📢✨ New journal publication alert! ✨📢 @OBohdal, @tmh31 , Phil @OxfordTVG , and I @FazlBarez have dissected a crucial issue: lack of #AIFairness. Our analysis reveals how unfair AI can fuel social stress and unrest over time. 🧵 Here are the main insights: [1/4]
We've also got papers at ICML workshops 🌺🌺🌺
- Will Toner: Label Noise: Correcting a Correction Loss arxiv.org/abs/2307.13100
- @OBohdal: Impact of Noise on Calibration and Generalisation of Neural Networks arxiv.org/abs/2306.17630
1/2
- @sillinuss: Why Do Self-Supervised Models Transfer? On Data Augmentation and Feature Properties icml.cc/virtual/2023/26959
- @sighellan: Bayesian Optimisation Against Climate Change: Applications and Benchmarks arxiv.org/abs/2306.04343
2/2
CDT in Data Science retweeted
Curious about how noise influences uncertainty calibration and generalisation of neural networks? We'll present our new work on this topic at the #ICML2023 SCIS workshop this Saturday! Collaboration with @MartinFerianc, @tmh31, @mrd_rodrigues
Hello from ICML'23! We will be presenting our joint work with @OBohdal, @tmh31, @mrd_rodrigues: Impact of Noise on Calibration and Generalisation of Neural Networks at the Spurious Correlations, Invariance, and Stability Workshop: arxiv.org/abs/2306.17630
The CDT has two papers at #ACL2023 this week thanks to @tomsherborne:
- Extrinsic Evaluation of Machine Translation Metrics: An outstanding paper! 🎉🎉🎉
- Meta-Learning a Cross-lingual Manifold for Semantic Parsing
Congratulations to CDT student Tom! 🎉🎉🎉
We won outstanding paper at @aclmeeting! Major thanks to my co-authors @nikita_moghe @alexandrabirch1 and Mark Steedman #ACL2023NLP #NLProc
CDT in Data Science retweeted
I'll be at #ACL2023 next week with 2 papers:
⭐️Extrinsic Evaluation of Machine Translation Metrics (Main conf - Monday Session 2: MT Oral)
⭐️Meta-Learning a Cross-lingual Manifold for Semantic Parsing (TACL - Wednesday Session 7: Semantics)
Reach out if you want to say hello!
CDT in Data Science retweeted
Finding yourself repeatedly training your ML model because you’ve collected more data? Not sure what to do with the hyperparameters? We investigated for you!
Check out the paper arxiv.org/abs/2306.16916 with the wonderful Huibin Shen, @FrancoisAubet, David Salinas and @kleiaaro