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19.07.2024

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Teaser image to MCML at ICML 2024

MCML at ICML 2024

26 Accepted Papers (17 Main, and 9 Workshops)

41st International Conference on Machine Learning, Vienna, Austria, Jul 21-27, 2024

We are happy to announce that MCML researchers have contributed a total of 26 papers to ICML 2024: 17 Main, and 9 Workshop papers. Congrats to our researchers!

Main Track (17 papers)

K. Bouchiat • A. Immer • H. Yèche • G. Ratsch • V. Fortuin
Improving Neural Additive Models with Bayesian Principles.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

M. Bini • K. Roth • Z. Akata • A. Khoreva
ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL GitHub

T. Decker • A. R. Bhattarai • J. Gu • V. Tresp • F. Buettner
Provably Better Explanations with Optimized Aggregation of Feature Attributions.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

S. Eckman • B. PlankF. Kreuter
Position: Insights from Survey Methodology can Improve Training Data.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

D. FrauenV. MelnychukS. Feuerriegel
Fair Off-Policy Learning from Observational Data.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

F. Fumagalli • M. MuschalikP. KolpaczkiE. Hüllermeier • B. Hammer
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

M. Herrmann • F. J. D. Lange • K. Eggensperger • G. CasalicchioM. WeverM. FeurerD. RügamerE. HüllermeierA.-L. BoulesteixB. Bischl
Position: Why We Must Rethink Empirical Research in Machine Learning.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

G. KaissisS. Kolek • B. Balle • J. Hayes • D. Rückert
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

F. Karl • M. Kemeter • G. Dax • P. Sierak
Position: Embracing Negative Results in Machine Learning.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

M. Lindauer • F. Karl • A. Klier • J. Moosbauer • A. Tornede • A. C. Mueller • F. Hutter • M. FeurerB. Bischl
Position: A Call to Action for a Human-Centered AutoML Paradigm.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

T. Papamarkou • M. Skoularidou • K. Palla • L. Aitchison • J. Arbel • D. Dunson • M. Filippone • V. Fortuin • P. Hennig • J. M. Hernández-Lobato • A. Hubin • A. Immer • T. Karaletsos • M. E. Khan • A. Kristiadi • Y. Li • S. Mandt • C. Nemeth • M. A. Osborne • T. G. J. Rudner • D. Rügamer • Y. W. Teh • M. Welling • A. G. Wilson • R. Zhang
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

D. RügamerC. KolbT. Weber • L. Kook • T. Nagler
Generalizing orthogonalization for models with non-linearities.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

Y. SaleV. Bengs • M. Caprio • E. Hüllermeier
Second-Order Uncertainty Quantification: A Distance-Based Approach.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

Y. Shen • N. Daheim • B. Cong • P. Nickl • G. M. Marconi • C. Bazan • R. Yokota • I. Gurevych • D. Cremers • M. E. Khan • T. Möllenhoff
Variational Learning is Effective for Large Deep Networks.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL GitHub

J. SchweisthalD. Frauen • M. Van der Schaar • S. Feuerriegel
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

E. SommerL. Wimmer • T. Papamarkou • L. BothmannB. BischlD. Rügamer
Connecting the Dots: Is Mode Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

D. Tramontano • Y. Kivva • S. Salehkaleybar • M. Drton • N. Kiyavash
Causal Effect Identification in LiNGAM Models with Latent Confounders.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

Workshops (9 papers)

M. Dani • M. J. Prakash • Z. Akata • S. Liebe
SemioLLM: Assessing Large Language Models for Semiological Analysis in Epilepsy Research.
AI4Science @ICML 2024 - AI for Science Workshop at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

P. Foth • L. Gosch • S. Geisler • L. Schwinn • S. Günnemann
Relaxing Graph Transformers for Adversarial Attacks.
Differentiable Almost Everything @ICML 2024 - Workshop Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. PDF

X. Feng • Z. Jiang • T. KaufmannE. Hüllermeier • P. Weng • Y. Zhu
Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries.
MHFAIA @ICML 2024 - Workshop on Models of Human Feedback for AI Alignment at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

U. Fischer AbaigarC. KernF. Kreuter
The Missing Link: Allocation Performance in Causal Machine Learning.
Workshop Humans, Algorithmic Decision-Making and Society @ICML 2024 - Workshop Humans, Algorithmic Decision-Making and Society: Modeling Interactions and Impact at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. arXiv URL

K. Flöge • M. A. Moeed • V. Fortuin
Stein Variational Newton Neural Network Ensembles.
SPIGM @ICML 2024 - Workshop on Structured Probabilistic Inference & Generative Modeling at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

P. HofmanY. SaleE. Hüllermeier
Quantifying Aleatoric and Epistemic Uncertainty: A Credal Approach.
SPIGM @ICML 2024 - Workshop on Structured Probabilistic Inference & Generative Modeling at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

Y. Sun • J. Liu • Z. Wu • Z. DingY. MaT. SeidlV. Tresp
SA-DQAS: Self-attention Enhanced Differentiable Quantum Architecture Search.
Differentiable Almost Everything @ICML 2024 - Workshop Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. PDF

F. Sergeev • P. Malsot • G. Rätsch • V. Fortuin
Towards Dynamic Feature Acquisition on Medical Time Series by Maximizing Conditional Mutual Information.
SPIGM @ICML 2024 - Workshop on Structured Probabilistic Inference & Generative Modeling at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

T. Uscidda • L. EyringK. RothF. J. TheisZ. Akata • M. Cuturi
Disentangled Representation Learning through Geometry Preservation with the Gromov-Monge Gap.
SPIGM @ICML 2024 - Workshop on Structured Probabilistic Inference & Generative Modeling at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. arXiv

#research #top-tier-work #akata #bischl #boulesteix #cremers #drton #feuerriegel #feurer #fortuin #guennemann #huellermeier #kaissis #kern #kreuter #kutyniok #nagler #plank #rueckert #ruegamer #seidl #theis #tresp

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