19.07.2024
24 Accepted Papers (17 Main, and 7 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 24 papers to ICML 2024: 17 Main, and 7 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
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
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
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. Plank • F. 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
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. Frauen • V. Melnychuk • S. Feuerriegel
Fair Off-Policy Learning from Observational Data.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL
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. Muschalik • P. Kolpaczki • E. 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
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. Casalicchio • M. Wever • M. Feurer • D. Rügamer • E. Hüllermeier • A.-L. Boulesteix • B. 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
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. Kaissis • S. 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
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
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. Feurer • B. 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
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
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. Rügamer • C. Kolb • T. 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
Generalizing orthogonalization for models with non-linearities.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL
Y. Sale • V. 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
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
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. Schweisthal • D. 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
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. Sommer • L. Wimmer • T. Papamarkou • L. Bothmann • B. Bischl • D. 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
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
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 (7 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
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
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. Kaufmann • E. 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
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 Abaigar • C. Kern • F. 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
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
P. Hofman • Y. Sale • E. 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
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. Ding • Y. Ma • T. Seidl • V. 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
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
T. Uscidda • L. Eyring • K. Roth • F. J. Theis • Z. 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
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
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