Morgane Austern

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 16

Top Topics

Unbiased Estimator

Kolmogorov Complexity

Top Venues

IEEE Trans. Inf. Theory

Publications

Suqi Liu, Morgane Austern
Random Geometric Graph Alignment with Graph Neural Networks. CoRR (2024)
Alan Chung, Amin Saberi, Morgane Austern
Statistical Guarantees for Link Prediction using Graph Neural Networks. CoRR (2024)
Qizhao Chen, Morgane Austern, Vasilis Syrgkanis
Inference on Optimal Dynamic Policies via Softmax Approximation. CoRR (2023)
Andrew Davison, Morgane Austern
Asymptotics of Network Embeddings Learned via Subsampling. J. Mach. Learn. Res. 24 (2023)
Qizhao Chen, Vasilis Syrgkanis, Morgane Austern
Debiased Machine Learning without Sample-Splitting for Stable Estimators. CoRR (2022)
Qizhao Chen, Vasilis Syrgkanis, Morgane Austern
Debiased Machine Learning without Sample-Splitting for Stable Estimators. NeurIPS (2022)
Kevin H. Huang, Peter Orbanz, Morgane Austern
Quantifying the Effects of Data Augmentation. CoRR (2022)
Andrew Davison, Morgane Austern
Asymptotics of Network Embeddings Learned via Subsampling. CoRR (2021)
Morgane Austern, Vasilis Syrgkanis
Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection. NeurIPS (2021)
Morgane Austern, Vasilis Syrgkanis
Asymptotics of the Empirical Bootstrap Method Beyond Asymptotic Normality. CoRR (2020)
Morgane Austern, Arian Maleki
On the Gaussianity of Kolmogorov Complexity of Mixing Sequences. IEEE Trans. Inf. Theory 66 (2) (2020)
Victor Veitch, Morgane Austern, Wenda Zhou, David M. Blei, Peter Orbanz
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data. AISTATS (2019)
Wenda Zhou, Victor Veitch, Morgane Austern, Ryan P. Adams, Peter Orbanz
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach. ICLR (Poster) (2019)
Victor Veitch, Morgane Austern, Wenda Zhou, David M. Blei, Peter Orbanz
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data. CoRR (2018)
Wenda Zhou, Victor Veitch, Morgane Austern, Ryan P. Adams, Peter Orbanz
Compressibility and Generalization in Large-Scale Deep Learning. CoRR (2018)
Morgane Austern, Arian Maleki
On the Gaussianity of Kolmogorov Complexity of Mixing Sequences. CoRR (2017)