Leena C. Vankadara

Affiliations:
  • University of Tübingen, Department of Computer Science, Germany
  • Max Planck Institute for Intelligent Systems (MPI-IS), Tübingen, Germany


According to our database1, Leena C. Vankadara authored at least 19 papers between 2016 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
On the Surprising Effectiveness of Large Learning Rates under Standard Width Scaling.
CoRR, May, 2025

2024
μ P<sup>2</sup>: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling.
CoRR, 2024

On Feature Learning in Structured State Space Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

μP<sup>2</sup>: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Explaining Kernel Clustering via Decision Trees.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Self-Compatibility: Evaluating Causal Discovery without Ground Truth.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Insights into Ordinal Embedding Algorithms: A Systematic Evaluation.
J. Mach. Learn. Res., 2023

Reinterpreting causal discovery as the task of predicting unobserved joint statistics.
CoRR, 2023

2022
A Consistent Estimator for Confounding Strength.
CoRR, 2022

Causal forecasting: generalization bounds for autoregressive models.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Interpolation and Regularization for Causal Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graphon based Clustering and Testing of Networks: Algorithms and Theory.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Causal Forecasting: Generalization Bounds for Autoregressive Models.
CoRR, 2021

Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
On the optimality of kernels for high-dimensional clustering.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Large scale representation learning from triplet comparisons.
CoRR, 2019

2018
Measures of distortion for machine learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016


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